Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Plant Ecology (programme PřF, N-BOT)
- Phycology and Mycology (programme PřF, N-BOT)
- Nature Conservation - Botany (programme PřF, N-OCH)
- Nature Conservation - Zoology (programme PřF, N-OCH)
- Zoology (programme PřF, N-ZOL)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of Sciencespring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Botany)
- 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
- 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/
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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/
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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/
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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/
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of Scienceautumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Ecological and Evolutionary Biology (programme PřF, B-EB)
- Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of Sciencespring 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceSpring 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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/
Bi7540 Data analysis in community ecology
Faculty of ScienceAutumn 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
- Biology - Museology (programme PřF, M-BI, specialization Botany)
- Systematic Biology and Ecology (programme PřF, B-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, M-BI, specialization Systematic Botany and Ecology)
- Systematic Biology and Ecology (programme PřF, N-BI, specialization Systematic Botany and Ecology)
- 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
- 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
- Enrolment Statistics (recent)