Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2024
Extent and Intensity
1/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
Mgr. Irena Axmanová, Ph.D. (lecturer)
Mgr. Kryštof Chytrý (lecturer)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 9:00–9:50 D32/329, Tue 15:00–16:50 B09/316
Prerequisites
Bi5560 Basic statistics for biol. II && ! Bi7542 Data anal. commun. ecology
Students need to be familiar with the R software including basic data manipulation and analysis, and graph plotting. Knowledge of at least basic statistics (ANOVA, simple linear regression) is required.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course introduces methods of statistical analysis of data on species composition of plant or animal communities, irrespective of their taxonomic delimitation. The principal course topics include advanced data manipulation techniques, analyses of diversity, ordination methods, and numerical classification. At the end of this course, students should be able to apply the methods discussed in the R environment.
Learning outcomes
Choose an appropriate statistical method to address questions concerning diversity and species composition of ecological communities;
Apply these methods;
Interpret the results;
Produce the graphical output illustrating the results;
Incorporate the analysis in a scientific text;
Syllabus
  • Data types in community ecology (community composition data, univariate community parameters, environmental condition) Data preparation for analysis, data formats and their conversions, exploratory data analysis.
  • Diversity indices and their dependence on environmental conditions (multiple regression), species accumulation curve, and rarefaction.
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination methods (linear vs unimodal, distance-based, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, covariates)
  • Designs of ecological experiments (observations vs. manipulative experiments)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive)
  • Practicals will consist of the analysis of real-world data in the software R.
Literature
  • Oksanen J. Vegan vignetes https://cran.r-project.org/web/packages/vegan/vignettes/
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
Teaching methods
Theoretical lessons with additional computer practicals.
Assessment methods
For the exam, students will prepare a short essay in which they analyze their own or demonstration data using the statistical approaches discussed in the course. The essay should have a form of methods and results of a scientific paper. Subsequently, students present the essays at a colloquium. The grade is based on the essay quality, presentation, and discussion at the colloquium.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2023
Extent and Intensity
1/2/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
Mgr. Irena Axmanová, Ph.D. (lecturer)
Mgr. Kryštof Chytrý (lecturer)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 9:00–9:50 D31/238, Tue 15:00–16:50 B09/316
Prerequisites
Bi5560 Basics of statistics for biol. && ! Bi7542 Data anal. commun. ecology
Students need to be familiar with the R software including basic data manipulation and analysis, and graph plotting. Knowledge of at least basic statistics (ANOVA, simple linear regression) is required.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course introduces methods of statistical analysis of data on species composition of plant or animal communities, irrespective of their taxonomic delimitation. The principal course topics include advanced data manipulation techniques, analyses of diversity, ordination methods, and numerical classification. At the end of this course, students should be able to apply the methods discussed in the R environment.
Learning outcomes
Choose an appropriate statistical method to address questions concerning diversity and species composition of ecological communities;
Apply these methods;
Interpret the results;
Produce the graphical output illustrating the results;
Incorporate the analysis in a scientific text;
Syllabus
  • Data types in community ecology (community composition data, univariate community parameters, environmental condition) Data preparation for analysis, data formats and their conversions, exploratory data analysis.
  • Diversity indices and their dependence on environmental conditions (multiple regression), species accumulation curve, and rarefaction.
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination methods (linear vs unimodal, distance-based, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, covariates)
  • Designs of ecological experiments (observations vs. manipulative experiments)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive)
  • Practicals will consist of the analysis of real-world data in the software R.
Literature
  • Oksanen J. Vegan vignetes https://cran.r-project.org/web/packages/vegan/vignettes/
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
Teaching methods
Theoretical lessons with additional computer practicals.
Assessment methods
For the exam, students will prepare a short essay in which they analyze their own or demonstration data using the statistical approaches discussed in the course. The essay should have a form of methods and results of a scientific paper. Subsequently, students present the essays at a colloquium. The grade is based on the essay quality, presentation, and discussion at the colloquium.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2023
Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: zk (examination). Other types of completion: k (colloquium).
Teacher(s)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 14:00–16:50 B09/316
Prerequisites
Bi5040 Biostatistics - basic course || Bi5560 Basics of statistics for biol.
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the popular R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2022
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 14:00–16:50 B09/316
Prerequisites
Bi5040 Biostatistics - basic course || Bi5560 Basics of statistics for biol.
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the popular R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://vitsyrovatka.info/doku.php?id=zpradat:cs:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2021
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Mon 1. 3. to Fri 14. 5. Tue 14:00–16:50 online_B6
Prerequisites
Bi5040 Biostatistics - basic course || Bi5560 Basics of statistics for biol.
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2020
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Jakub Těšitel, Ph.D. (lecturer)
Guaranteed by
doc. RNDr. Jakub Těšitel, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: doc. RNDr. Jakub Těšitel, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 14:00–16:50 B09/316
Prerequisites
Bi5040 Biostatistics - basic course || Bi5560 Basics of statistics for biol.
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the popular R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://vitsyrovatka.info/doku.php?id=zpradat:cs:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2019
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vít Syrovátka, Ph.D. (lecturer)
Guaranteed by
Mgr. Vít Syrovátka, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. Vít Syrovátka, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Mon 18. 2. to Fri 17. 5. Tue 12:00–13:50 B09/316, Thu 10:00–11:50 D36/225
Prerequisites
Bi5040 Biostatistics - basic course
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the popular R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://vitsyrovatka.info/doku.php?id=zpradat:cs:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
spring 2018
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vít Syrovátka, Ph.D. (lecturer)
Guaranteed by
Mgr. Vít Syrovátka, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. Vít Syrovátka, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Mon 16:00–17:50 B09/316, Wed 11:00–12:50 D32/329
Prerequisites
Bi5040 Biostatistics - basic course
The lecture expects a basic statistical knowledge in the extent of the basic Bi5040 Biostatistics course, namely correlation analysis, and (generalized) linear models. It is therefore recommended that students enroll this class after the Biostatistics course. The practicals will be taught in the popular R software. Previous basic knowledge of work in R is also recommended. Such knowledge may be achieved in the Bi7560 Introduction to R course.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using a popular program R.
Learning outcomes
Students should be able to:
Choose an appropriate multidimensional method to solve a given ecological problem
Apply this method
Interpret the results
Accompany the results with an illustrative graphical output
Incorporate the analysis into a scientific text
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Practicals will consist of the analysis of real-world data in the software R.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
    not specified
  • ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
  • BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info
  • ZUUR, Alain F., Elena N. IENO and Graham M. SMITH. Analysing Ecological Data. Springer-Verlag New York, 2007, 672 pp. ISBN 978-0-387-45967-7. Available from: https://dx.doi.org/10.1007/978-0-387-45972-1. URL info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://vitsyrovatka.info/doku.php?id=zpradat:cs:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2017
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vít Syrovátka, Ph.D. (lecturer)
Guaranteed by
Mgr. Vít Syrovátka, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. Vít Syrovátka, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Mon 20. 2. to Mon 22. 5. Mon 9:00–12:50 B09/316, Mon 17:00–18:50 D32/329
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO 5 and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://vitsyrovatka.info/doku.php?id=zpradat:cs:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2016
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. Vít Syrovátka, Ph.D. (lecturer)
Guaranteed by
Mgr. Vít Syrovátka, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. Vít Syrovátka, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Mon 17:00–18:50 D32/329, Fri 8:00–11:50 B09/316
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO 5 and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2015
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 14:00–15:50 B11/333, Fri 8:00–11:50 B09/316
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis), types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Ordination (linear vs unimodal, constrained vs unconstrained, ordination diagrams, permutation tests, variance partitioning, forward selection, case studies)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Use of species functional traits or species indicator values in multivariate analysis (functional traits, Ellenberg indicator values, community-weighted mean, fourth-corner)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Design of ecological experiments (manipulative vs natural experiments)
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO 5 and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2014
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 12:00–13:50 B11/235, Fri 8:00–11:50 B09/316
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2013
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 11:00–12:50 BR2, Fri 8:00–11:50 B09/316
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorial vs quantitative, abundances, frequences)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, aglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Regression (Generalized linear models, Classification and regression trees)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alfa, beta and gama diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computar labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons (which will take place every week in Reckovice) with additional computer labs (three to four blocks in Bohunice computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/zeleny/wiki/david-wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2012
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Timetable
Tue 8:00–9:50 BR4, Tue 16:00–19:50 B09/316
Prerequisites (in Czech)
( Bi5040 Biostatistics - basic course )||(SOUHLAS)
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorial vs quantitative, abundances, frequences)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, aglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Regression (Generalized linear models, Classification and regression trees)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alfa, beta and gama diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computar labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons (which will take place every week in Reckovice) with additional computer labs (three to four blocks in Bohunice computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/zeleny/wiki/david-wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2011
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Timetable
Tue 14:00–15:50 BR2, Fri 10:00–11:50 B09/316
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica.
Syllabus
  • Design of ecological experiments (manipulative vs empirical experiments)
  • Types of data (categorial vs quantitative, abundances, frequences)
  • How to prepare data for numerical analysis (data cleaning, detection of outliers, transformation, standardization, EDA)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Classification (hierarchical vs nonhierarchical, aglomerative vs divisive, supervised vs unsupervised, COCKTAIL)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Regression (Generalized linear models, Classification and regression trees)
  • Ellenberg indicator values (calibration, pitfalls)
  • Species richness (alfa, beta and gama diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Computar labs will provide opportunity to improve practical software knowledge with programs like STATISTICA, PC-ORD, CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons (which will take place every week in Reckovice) with additional computer labs (once per two weeks in Bohunice)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2010
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Timetable
Mon 13:00–14:50 BR2
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Follow-Up Courses
Further Comments
Study Materials
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/zeleny/zpradat/
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2008
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Wed 8:00–9:50 BR2
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Při výkladu místy navazuji na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a proto budu raději, když studenti tento předmět zapíší až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO, Statistica etc.
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods
Lessons include explanation of theory and demonstration of computer programs. For exam students prepare classification and ordination analyses of their own data or data obtained from the teacher, which they summarize in a brief report. The exam is oral discussion about this report. Students are required to know the theory in the background of individual methods. For more detailed requirements see http://www.sci.muni.cz/botany/chytry/zpradat/uloha.htm.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/chytry/zpradat/
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2007
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Tue 8:00–9:50 BR4
Prerequisites
Bi5040 Biostatistics - basic course
Při výkladu místy navazuji na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a proto budu raději, když studenti tento předmět zapíší až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, CANOCO, Statistica a další.
Syllabus
  • 1. Introduction to community ecology methods. 2. Field sampling design. 3. Data handling: computer programs. 4. Data standardizations and transformations. 5. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN). 6. Theory of gradient analysis. 7. Regression models including regression trees (CART). 8. Calibration and bioindication. 9. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA). 10. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations. 11. Computer programs PC-ORD, CANOCO, Statistica. 12. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. Ke zkoušce student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké písemné zprávy. Pro úspěšné složení zkoušky je nutná znalost teorie v pozadí jednotlivých metod. Podrobnější požadavky viz http://www.sci.muni.cz/botany/chytry/zpradat/uloha.htm.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/chytry/zpradat/
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2006
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Tue 17:00–18:50 BR4
Prerequisites
( Bi5040 Biostatistics - basic course || B5040 Biostatistics )&&(! B7540 Data anal. commun. ecology )
Při výkladu místy navazuji na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a proto budu raději, když studenti tento předmět zapíší až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, CANOCO, Statistica a další.
Syllabus
  • 1. Introduction to community ecology methods. 2. Field sampling design. 3. Data handling: computer programs. 4. Data standardizations and transformations. 5. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN). 6. Theory of gradient analysis. 7. Regression models including regression trees (CART). 8. Calibration and bioindication. 9. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA). 10. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations. 11. Computer programs PC-ORD, CANOCO, Statistica. 12. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. Ke zkoušce student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké písemné zprávy. Pro úspěšné složení zkoušky je nutná znalost teorie v pozadí jednotlivých metod. Podrobnější požadavky viz http://www.sci.muni.cz/botany/chytry/zpradat/uloha.htm.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/chytry/zpradat/
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2005
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Tue 14:00–15:50 02002
Prerequisites (in Czech)
( Bi5040 Biostatistics - basic course || B5040 Biostatistics )&&(! B7540 Data anal. commun. ecology )
Pro dobré porozumění probírané látce je vhodné absolvovat předmět B5040 Biostatistika. Užitečné, nikoliv ale nezbytné, je dřívější absolvování předmětu B6549 Metody fytocenologie.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, SYN-TAX, CANOCO, SPSS, and some others.
Syllabus
  • Introduction to community ecology.
  • Field sampling, sampling design.
  • Data handling: computer programs.
  • Pattern analysis: distance and blocked-quadrat methods.
  • Measuring community diversity.
  • Standardizations and transformations of data.
  • Numerical classification - cluster analysis and TWINSPAN.
  • Gradient analysis.
  • Regression.
  • Calibration.
  • Ordination - PCA, CA, DCA.
  • Constrained ordination - CCA.
  • Statistical models of succession - Markov chains.
  • Computer programs SYN-TAX, CANOCO, SPSS, TURBEK, TWINSPAN.
  • Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. K zápočtu student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké zprávy v angličtině. K zápočtu je rovněž požadována teorie v pozadí jednotlivých metod.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2004
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Timetable
Tue 10:00–11:50 02002
Prerequisites (in Czech)
( Bi5040 Biostatistics - basic course || B5040 Biostatistics )&&(! B7540 Data anal. commun. ecology )
Pro dobré porozumění probírané látce je vhodné absolvovat předmět B5040 Biostatistika. Užitečné, nikoliv ale nezbytné, je dřívější absolvování předmětu B6549 Metody fytocenologie.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, SYN-TAX, CANOCO, SPSS, and some others.
Syllabus
  • Introduction to community ecology.
  • Field sampling, sampling design.
  • Data handling: computer programs.
  • Pattern analysis: distance and blocked-quadrat methods.
  • Measuring community diversity.
  • Standardizations and transformations of data.
  • Numerical classification - cluster analysis and TWINSPAN.
  • Gradient analysis.
  • Regression.
  • Calibration.
  • Ordination - PCA, CA, DCA.
  • Constrained ordination - CCA.
  • Statistical models of succession - Markov chains.
  • Computer programs SYN-TAX, CANOCO, SPSS, TURBEK, TWINSPAN.
  • Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. K zápočtu student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké zprávy v angličtině. K zápočtu je rovněž požadována teorie v pozadí jednotlivých metod.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2003
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Prerequisites (in Czech)
( Bi5040 Biostatistics - basic course || B5040 Biostatistics )&&(! B7540 Data anal. commun. ecology )
Pro dobré porozumění probírané látce je vhodné absolvovat předmět B5040 Biostatistika. Užitečné, nikoliv ale nezbytné, je dřívější absolvování předmětu B6549 Metody fytocenologie.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, SYN-TAX, CANOCO, SPSS, and some others.
Syllabus
  • Introduction to community ecology.
  • Field sampling, sampling design.
  • Data handling: computer programs.
  • Pattern analysis: distance and blocked-quadrat methods.
  • Measuring community diversity.
  • Standardizations and transformations of data.
  • Numerical classification - cluster analysis and TWINSPAN.
  • Gradient analysis.
  • Regression.
  • Calibration.
  • Ordination - PCA, CA, DCA.
  • Constrained ordination - CCA.
  • Statistical models of succession - Markov chains.
  • Computer programs SYN-TAX, CANOCO, SPSS, TURBEK, TWINSPAN.
  • Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. K zápočtu student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké zprávy v angličtině. K zápočtu je rovněž požadována teorie v pozadí jednotlivých metod.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2002
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Prerequisites (in Czech)
( Bi5040 Biostatistics - basic course || B5040 Biostatistics )&&(! B7540 Data anal. commun. ecology )
Pro dobré porozumění probírané látce je vhodné absolvovat předmět B5040 Biostatistika. Užitečné, nikoliv ale nezbytné, je dřívější absolvování předmětu B6549 Metody fytocenologie.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, SYN-TAX, CANOCO, SPSS, and some others.
Syllabus
  • Introduction to community ecology.
  • Field sampling, sampling design.
  • Data handling: computer programs.
  • Pattern analysis: distance and blocked-quadrat methods.
  • Measuring community diversity.
  • Standardizations and transformations of data.
  • Numerical classification - cluster analysis and TWINSPAN.
  • Gradient analysis.
  • Regression.
  • Calibration.
  • Ordination - PCA, CA, DCA.
  • Constrained ordination - CCA.
  • Statistical models of succession - Markov chains.
  • Computer programs SYN-TAX, CANOCO, SPSS, TURBEK, TWINSPAN.
  • Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. K zápočtu student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké zprávy v angličtině. K zápočtu je rovněž požadována teorie v pozadí jednotlivých metod.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2018

The course is not taught in Autumn 2018

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
autumn 2017

The course is not taught in autumn 2017

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2016

The course is not taught in Autumn 2016

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2015

The course is not taught in Autumn 2015

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2014

The course is not taught in Autumn 2014

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2013

The course is not taught in Autumn 2013

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Přednáška navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může si předmět zapsat a na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomic delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages (such as CANOCO and CanoDraw).
Syllabus
  • Pre-analysis data preparation (data cleaning, outliers, transformation, standardization, exploratory data analysis)
  • Design of ecological experiments (manipulative vs natural experiments)
  • Types of data (categorical vs quantitative, abundances, frequencies)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Numerical classification (hierarchical vs nonhierarchical, agglomerative vs divisive, supervised vs unsupervised)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Calibration (Ellenberg indicator values and their pitfalls)
  • Diversity indices (alpha, beta and gamma diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
    Computer labs will provide opportunity to improve practical software knowledge with programs CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
    recommended literature
  • LEPŠ, Jan a Petr ŠMILAUER. Mnohorozměrná analýza ekologických dat. 2001. http://regent.jcu.cz/skripta.pdf
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs (three to four blocks in computer lab)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional questions targeting theoretical background of used methods.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.davidzeleny.net/wiki/doku.php?id=zpradat:start
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2012

The course is not taught in Autumn 2012

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2011

The course is not taught in Autumn 2011

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
there are 6 fields of study the course is directly associated with, display
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2010

The course is not taught in Autumn 2010

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2009

The course is not taught in Autumn 2009

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
spring 2012 - acreditation

The information about the term spring 2012 - acreditation is not made public

Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Supplier department: Department of Botany and Zoology – Biology Section – Faculty of Science
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica.
Syllabus
  • Design of ecological experiments (manipulative vs empirical experiments)
  • Types of data (categorial vs quantitative, abundances, frequences)
  • How to prepare data for numerical analysis (data cleaning, detection of outliers, transformation, standardization, EDA)
  • Ecological similarity (indices of ecological similarity and distance between samples)
  • Classification (hierarchical vs nonhierarchical, aglomerative vs divisive, supervised vs unsupervised, COCKTAIL)
  • Ordination (linear vs unimodal, constrained vs unconstrained)
  • Regression (Generalized linear models, Classification and regression trees)
  • Ellenberg indicator values (calibration, pitfalls)
  • Species richness (alfa, beta and gama diversity, accumulation curves and rarefaction curves)
  • Case studies demonstrating the use of particular analytical methods
  • Computar labs will provide opportunity to improve practical software knowledge with programs like STATISTICA, PC-ORD, CANOCO and CANODRAW and to apply acquired theoretical knowledge about analytical methods on real ecological data.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons (which will take place every week in Reckovice) with additional computer labs (once per two weeks in Bohunice)
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2011 - acreditation

The information about the term Autumn 2011 - acreditation is not made public

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Spring 2011 - only for the accreditation
Extent and Intensity
2/1/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica.
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
theoretical lessons with additional computer labs
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper - more details about its structure will be published on the class website. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Follow-Up Courses
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2007 - for the purpose of the accreditation
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Milan Chytrý, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Milan Chytrý, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Milan Chytrý, Ph.D.
Prerequisites
Bi5040 Biostatistics - basic course
Při výkladu místy navazuji na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a proto budu raději, když studenti tento předmět zapíší až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors. The course includes training in using standard software packages such as PC-ORD, CANOCO, Statistica a další.
Syllabus
  • 1. Introduction to community ecology methods. 2. Field sampling design. 3. Data handling: computer programs. 4. Data standardizations and transformations. 5. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN). 6. Theory of gradient analysis. 7. Regression models including regression trees (CART). 8. Calibration and bioindication. 9. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA). 10. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations. 11. Computer programs PC-ORD, CANOCO, Statistica. 12. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Assessment methods (in Czech)
Ve výuce je vysvětlována teorie a předváděny počítačové programy. Ke zkoušce student zpracovává soubor dat, buď svých vlastních nebo dat od učitele, pomocí probíraných klasifikačních a ordinačních metod. Zpracované analýzy předkládá ve formě krátké písemné zprávy. Pro úspěšné složení zkoušky je nutná znalost teorie v pozadí jednotlivých metod. Podrobnější požadavky viz http://www.sci.muni.cz/botany/chytry/zpradat/uloha.htm.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
Teacher's information
http://www.sci.muni.cz/botany/chytry/zpradat/
The course is also listed under the following terms Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.

Bi7540 Data analysis in community ecology

Faculty of Science
Autumn 2010 - only for the accreditation

The course is not taught in Autumn 2010 - only for the accreditation

Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Teacher(s)
Mgr. David Zelený, Ph.D. (lecturer)
Guaranteed by
Mgr. David Zelený, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: Mgr. David Zelený, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Výklad navazuje na znalosti získané v předmětu Bi5040 Biostatistika, zejména na regresní analýzu a obecné lineární modely, a bylo by proto lepší, aby si studenti tento předmět zapsali až po absolvování Biostatistiky. Pokud chce student i přesto tento předmět navštěvovat (např. aby se naučil analytické metody nutné pro zpracování bakalářské práce), může na přednášky chodit s tím, že se individuálně domluvíme na způsobu ukončení předmětu (např. zkoušku uděláme až po zkoušce z Biostatistiky nebo v dalším školním roce). Užitečné, nikoliv však nezbytné, je také předchozí absolvování předmětu Bi6549 Zpracování základních botanických dat.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course deals with basic methods of statistical analysis of the data on species composition of plant and animal communities, irrespective of their taxonomical delimitation. The focus is on numerical classification and ordination methods and analysis of the relationships between species composition and environmental factors.
At the end of this course, students should be able to apply particular methods, using standard software packages such as PC-ORD, CANOCO and Statistica. And becouse I believe that the future of data analysis is in R program, each lecture will have a short "five minutes with R" part - short demonstration of particular statistical methods in the environment of R program (however, knowledge of R and it's active use will not be either required or expected).
Syllabus
  • 1. Introduction to community ecology methods.
  • 2. Field sampling design.
  • 3. Data handling: computer programs.
  • 4. Data standardizations and transformations.
  • 5. Resemblance coefficients
  • 6. Numerical classification - cluster analysis and TWINSPAN. Supervised classification with artificial neural networks (ANN).
  • 7. Theory of gradient analysis.
  • 8. Regression models including regression trees (CART).
  • 9. Calibration and bioindication.
  • 10. Ordination - principal components analysis (PCA), correspondence analysis (CA), detrended correspondence analysis (DCA).
  • 11. Constrained ordination - redundancy analysis (RDA), canonical correspondence analysis (CCA), evaluation of ecological experiments with RDA and CCA, partial ordinations.
  • 12. Computer programs PC-ORD, CANOCO, Statistica.
  • 13. Case studies.
Literature
  • LEPŠ, Jan and Petr ŠMILAUER. Multivariantní analýza ekologických dat. 2001. info
  • HERBEN, Tomáš and Zuzana MÜNZBERGOVÁ. Zpracování geobotanických dat v příkladech. Část I. Data o druhovém složení. http://www.natur.cuni.cz/~botanika/, 2001. info
Teaching methods
frontal lecture, which combines theory with demonstration of statistical software
Assessment methods
For exam, students will prepare a short study, in which they analyze their own or demonstration data, using the statistical approaches discussed in the lecture. The study should have a form of short scientific paper. The exam is oral discussion about the study, with additional broadening questions, which should prove that student haven't slept during the lecture.
Language of instruction
Czech
Further Comments
The course can also be completed outside the examination period.
The course is taught annually.
The course is taught: every week.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Spring 2011 - only for the accreditation, Autumn 2002, Autumn 2003, Autumn 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Spring 2010, Spring 2011, Spring 2012, Autumn 2011 - acreditation, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022, Spring 2023, Autumn 2023, Autumn 2024.
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