Course Information

Bi7550 Practical Analysis of Biological Data – Seminar

Extent and Intensity

0/2/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).

Teacher(s)

Mgr. Kateřina Kintrová, Ph.D. (seminar tutor)
prof. Mgr. Stanislav Pekár, Ph.D. (seminar tutor)
doc. RNDr. Jakub Těšitel, Ph.D. (seminar tutor)

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

Fri 10:00–11:50 D31/238

Prerequisites

Bi5560 Basic statistics for biol. II || Bi6050 Introduction to Biostatistics
Students are required to have their own research data at the beginning of the course.
Students need to be familiar with the R software including data manipulation and analysis, and graph plotting.
Knowledge of at least basic statistics (ANOVA, linear regression, general linear models) is required.
Besides compulsory prerequisities (Bi5560 or Bi6050), we recommend to complete some advanced course (Bi7540 or Bi7920, optionally Bi7921) before this seminar.

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 16 fields of study the course is directly associated with, display

Course objectives

The course aims at guiding the students through the analysis of data originating from their own research during Master or PhD studies. The course facilitates the choosing and appropriate use of statistical tools in master/Ph.D. research and improves students’ skills in the presentation of data and analysis results. An essential aspect of the course is experience sharing among the students and discussions of the strategies of analysis.
The course specifically focuses on advanced data analyses such as multiple regression, multivariate statistics, analysis of structured data, etc. Individual topics will be discussed based on the nature of the students’ data.

Learning outcomes

After completing the course, the students will be able to: choose an appropriate method/model, discuss, interpret, and present the results of analysis (including the graphical outputs) in a way suitable for a scientific publication.

Syllabus

• 1. Introduction: presentations of students introducing their research data in the first two classes.
• 2. Group work on the data analysis. Students analyze their data and help the other with the analysis under the supervision of the course teachers. This part will extend across 2/3 of the semester.
• 3. Discussion of interesting topics and common problems of data analysis. Enriched by ad-hoc presentations contributed by teachers or students.
• 4. Presentation of the analysis results in the last two classes.

Literature

• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 1 - 1. díl. Zobecněné lineární modely v prostředí R. 2. přepracované vydání. Brno: Masarykova univerzita, 2020, 278 pp. ISBN 978-80-210-9622-6. info
• ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 2. Lineární modely s korelacemi v prostředí R (Modern Analysis of Biological Data 2. Linear Models with Correlations in R). 1st ed. Brno: Masarykova universita, 2012, 256 pp. ISBN 978-80-210-5812-5. info
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. 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

Weekly practicals dedicated to the presentation of the research or data analysis conducted in the R software. Students are required to bring their OWN LAPTOP.

Assessment methods

Active participation in the practicals is required. Essay structured as methods and results sections of a research paper/thesis supported by high-quality graphical outputs based on the analysis of student’s data.

Language of instruction

English

Further Comments

Study Materials
The course can also be completed outside the examination period.
The course is taught annually.

Bi7550 Practical Analysis of Biological Data – Seminar

Extent and Intensity

0/2/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).

Teacher(s)

Mgr. Kateřina Kintrová, Ph.D. (seminar tutor)
prof. Mgr. Stanislav Pekár, Ph.D. (seminar tutor)
doc. RNDr. Jakub Těšitel, Ph.D. (seminar tutor)

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

Fri 9:00–10:50 D31/238

Prerequisites

Bi5560 Basics of statistics for biol. || Bi6050 Introduction to Biostatistics
Students are required to have their own research data at the beginning of the course.
Students need to be familiar with the R software including data manipulation and analysis, and graph plotting.
Knowledge of at least basic statistics (ANOVA, linear regression, general linear models) is required.
Besides compulsory prerequisities (Bi5560 or Bi6050), we recommend to complete some advanced course (Bi7540 or Bi7920, optionally Bi7921) before this seminar.

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 16 fields of study the course is directly associated with, display

Course objectives

The course aims at guiding the students through the analysis of data originating from their own research during Master or PhD studies. The course facilitates the choosing and appropriate use of statistical tools in master/Ph.D. research and improves students’ skills in the presentation of data and analysis results. An essential aspect of the course is experience sharing among the students and discussions of the strategies of analysis.
The course specifically focuses on advanced data analyses such as multiple regression, multivariate statistics, analysis of structured data, etc. Individual topics will be discussed based on the nature of the students’ data.

Learning outcomes

After completing the course, the students will be able to: choose an appropriate method/model, discuss, interpret, and present the results of analysis (including the graphical outputs) in a way suitable for a scientific publication.

Syllabus

• 1. Introduction: presentations of students introducing their research data in the first two classes.
• 2. Group work on the data analysis. Students analyze their data and help the other with the analysis under the supervision of the course teachers. This part will extend across 2/3 of the semester.
• 3. Discussion of interesting topics and common problems of data analysis. Enriched by ad-hoc presentations contributed by teachers or students.
• 4. Presentation of the analysis results in the last two classes.

Literature

• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 1 - 1. díl. Zobecněné lineární modely v prostředí R. 2. přepracované vydání. Brno: Masarykova univerzita, 2020, 278 pp. ISBN 978-80-210-9622-6. info
• ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 2. Lineární modely s korelacemi v prostředí R (Modern Analysis of Biological Data 2. Linear Models with Correlations in R). 1st ed. Brno: Masarykova universita, 2012, 256 pp. ISBN 978-80-210-5812-5. info
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. 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

Weekly practicals dedicated to the presentation of the research or data analysis conducted in the R software. Students are required to bring their OWN LAPTOP.

Assessment methods

Active participation in the practicals is required. Essay structured as methods and results sections of a research paper/thesis supported by high-quality graphical outputs based on the analysis of student’s data.

Language of instruction

English

Further Comments

Study Materials
The course can also be completed outside the examination period.
The course is taught annually.

Bi7550 Practical Analysis of Biological Data – Seminar

Extent and Intensity

0/2/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).

Teacher(s)

Mgr. Kateřina Kintrová, Ph.D. (seminar tutor)
prof. Mgr. Stanislav Pekár, Ph.D. (seminar tutor)
doc. RNDr. Jakub Těšitel, Ph.D. (seminar tutor)

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

Wed 12:00–13:50 D31/238

Prerequisites

Bi5560 Basics of statistics for biol. || Bi6050 Introduction to Biostatistics
Students are required to have their own research data at the beginning of the course.
Students need to be familiar with the R software including data manipulation and analysis, and graph plotting.
Knowledge of at least basic statistics (ANOVA, linear regression, general linear models) is required.
Besides compulsory prerequisities (Bi5560 or Bi6050), we recommend to complete some advanced course (Bi7540 or Bi7920, optionally Bi7921) before this seminar.

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 16 fields of study the course is directly associated with, display

Course objectives

The course aims at guiding the students through the analysis of data originating from their own research during Master or PhD studies. The course facilitates the choosing and appropriate use of statistical tools in master/Ph.D. research and improves students’ skills in the presentation of data and analysis results. An essential aspect of the course is experience sharing among the students and discussions of the strategies of analysis.
The course specifically focuses on advanced data analyses such as multiple regression, multivariate statistics, analysis of structured data, etc. Individual topics will be discussed based on the nature of the students’ data.

Learning outcomes

After completing the course, the students will be able to: choose an appropriate method/model, discuss, interpret, and present the results of analysis (including the graphical outputs) in a way suitable for a scientific publication.

Syllabus

• 1. Introduction: presentations of students introducing their research data in the first two classes.
• 2. Group work on the data analysis. Students analyze their data and help the other with the analysis under the supervision of the course teachers. This part will extend across 2/3 of the semester.
• 3. Discussion of interesting topics and common problems of data analysis. Enriched by ad-hoc presentations contributed by teachers or students.
• 4. Presentation of the analysis results in the last two classes.

Literature

• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 1 - 1. díl. Zobecněné lineární modely v prostředí R. 2. přepracované vydání. Brno: Masarykova univerzita, 2020, 278 pp. ISBN 978-80-210-9622-6. info
• ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 2. Lineární modely s korelacemi v prostředí R (Modern Analysis of Biological Data 2. Linear Models with Correlations in R). 1st ed. Brno: Masarykova universita, 2012, 256 pp. ISBN 978-80-210-5812-5. info
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. 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

Weekly practicals dedicated to the presentation of the research or data analysis conducted in the R software. Students are required to bring their OWN LAPTOP.

Assessment methods

Active participation in the practicals is required. Essay structured as methods and results sections of a research paper/thesis supported by high-quality graphical outputs based on the analysis of student’s data.

Language of instruction

English

Further Comments

Study Materials
The course can also be completed outside the examination period.
The course is taught annually.

Bi7550 Practical Analysis of Biological Data – Seminar

Extent and Intensity

0/2/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: k (colloquium).

Teacher(s)

Mgr. Kateřina Kintrová, Ph.D. (seminar tutor)
prof. Mgr. Stanislav Pekár, Ph.D. (seminar tutor)
doc. RNDr. Jakub Těšitel, Ph.D. (seminar tutor)

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

Wed 12:00–13:50 D31/238

Prerequisites

Bi5560 Basics of statistics for biol. || Bi6050 Introduction to Biostatistics
Students are required to have their own research data at the beginning of the course.
Students need to be familiar with the R software including data manipulation and analysis, and graph plotting.
Knowledge of at least basic statistics (ANOVA, linear regression, general linear models) is required.
Besides compulsory prerequisities (Bi5560 or Bi6050), we recommend to complete some advanced course (Bi7540 or Bi7920, optionally Bi7921) before this seminar.

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 16 fields of study the course is directly associated with, display

Course objectives

The course aims at guiding the students through the analysis of data originating from their own research during Master or PhD studies. The course facilitates the choosing and appropriate use of statistical tools in master/Ph.D. research and improves students’ skills in the presentation of data and analysis results. An essential aspect of the course is experience sharing among the students and discussions of the strategies of analysis.
The course specifically focuses on advanced data analyses such as multiple regression, multivariate statistics, analysis of structured data, etc. Individual topics will be discussed based on the nature of the students’ data.

Learning outcomes

After completing the course, the students will be able to: choose an appropriate method/model, discuss, interpret, and present the results of analysis (including the graphical outputs) in a way suitable for a scientific publication.

Syllabus

• 1. Introduction: presentations of students introducing their research data in the first two classes.
• 2. Group work on the data analysis. Students analyze their data and help the other with the analysis under the supervision of the course teachers. This part will extend across 2/3 of the semester.
• 3. Discussion of interesting topics and common problems of data analysis. Enriched by ad-hoc presentations contributed by teachers or students.
• 4. Presentation of the analysis results in the last two classes.

Literature

• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 1 - 1. díl. Zobecněné lineární modely v prostředí R. 2. přepracované vydání. Brno: Masarykova univerzita, 2020, 278 pp. ISBN 978-80-210-9622-6. info
• ŠMILAUER, Petr and Jan LEPŠ. Multivariate Analysis of Ecological Data using CANOCO 5. 2nd ed. Cambridge: University Press, 2014, xii, 362. ISBN 9781107694408. info
• PEKÁR, Stanislav and Marek BRABEC. Moderní analýza biologických dat 2. Lineární modely s korelacemi v prostředí R (Modern Analysis of Biological Data 2. Linear Models with Correlations in R). 1st ed. Brno: Masarykova universita, 2012, 256 pp. ISBN 978-80-210-5812-5. info
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. 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

Weekly practicals dedicated to the presentation of the research or data analysis conducted in the R software. Students are required to bring their OWN LAPTOP.

Assessment methods

Active participation in the practicals is required. Essay structured as methods and results sections of a research paper/thesis supported by high-quality graphical outputs based on the analysis of student’s data.

Language of instruction

English

Further Comments

Study Materials
The course can also be completed outside the examination period.
The course is taught annually.

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 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

Timetable

Fri 8:00–11:50 B09/316

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Trait vs environment analysis (community-weighted mean, fourth-corner problem, RLQ).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it - in any case, teaching materials for these topics will be provided.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Online study materials (in English) include detail overview of the methods taught in the class, example data, exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...

Teacher's information

http://www.davidzeleny.net/anadat-r/doku.php/en:anadat-r

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 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

Timetable

Fri 8:00–11:50 B09/316

Prerequisites

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 9 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 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

Fri 8:00–9:50 B09/316

Prerequisites

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.).

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, B-BI, specialization Systematic Zoology and Ecology)
• Systematic Biology and Ecology (programme PřF, N-BI, specialization Botany)
• Systematic Biology and Ecology (programme PřF, N-BI, specialization Zoology)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Additional methods (e.g. Beals smoothing, diversity analysis such as rarefaction curves, etc.)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• CRAWLEY, Michael J. The R book. Chichester: Wiley, 2007, viii, 942. ISBN 9780470510247. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized).

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Spring 2021

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2020

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2019

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Spring 2019

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: Náplň předmětu včleněna do Bi7540 Zpracování dat v ekologii společenstev.
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2018

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in spring 2018

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in autumn 2017

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2016

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Spring 2016

Extent and Intensity

1/1/0. 2 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

Prerequisites

Bi7540 Data anal. commun. ecology ||NOW( Bi7540 Data anal. commun. ecology )
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• Introduction, data import, vegan library, recommended references, details about final examination.
• Unconstrained ordination (CA, PCA, DCA, PCoA, NMDS, drawing ordination diagrams, environmental variables in unconstrained ordination).
• Constrained ordination (RDA, CCA, db-RDA).
• Monte Carlo permutation test, forward selection, variance partitioning.
• Numerical classification (hierarchical and non-hierarchical classification, dendrogram, evaluation of classification results, indicator species).
• Optional: Trait vs environment analysis (community-weighted mean, fourth-corner problem, RLQ).
• Optional: Analysis of diversity (alpha and beta diversity, rarefaction curves). Note: optional topics will be inserted in case that participants are interested and there is enough time for it - in any case, teaching materials for these topics will be provided.

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Online study materials (in English) include detail overview of the methods taught in the class, example data, exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods introduced in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

English

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.davidzeleny.net/anadat-r/doku.php/en:anadat-r

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2015

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
Course is no more offered.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2014

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Spring 2014

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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

• Botany (programme PřF, N-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Botany)
• Ecological and Evolutionary Biology (programme PřF, B-EB, specialization Zoology)
• Zoology (programme PřF, N-EB)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2013

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester, although from formal reason you need to apply for exception - this will be automatically granted), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.). In case that enrolled students have no experience with using of R program, I will at the beginning insert one class devoted to "simple guide to R", which should ensure that everybody will have basic ability to master R program for the purpose of this class.

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 11 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Diversity indices (alpha and beta diversity)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• BORCARD, Daniel, François GILLET and Pierre LEGENDRE. Numerical ecology with R. New York: Springer, 2011, xi, 306. ISBN 9781441979759. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized). The class will be held once per two weeks in Bohunice computer room. Basic part of study materials is website, containing detailed overview of the methods taught in the class including guidelines for exercises and their solutions.

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Teacher's information

http://www.sci.muni.cz/botany/zeleny/wiki/anadat-r/doku.php?id=cs:start

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2012

Extent and Intensity

1/1/0. 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)

Bi7540 Data anal. commun. ecology

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 11 fields of study the course is directly associated with, display

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Spring 2012

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.).

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 9 fields of study the course is directly associated with, display

Course objectives

At the end of the class, students should be able to analyze various types of community ecology data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Additional methods (e.g. Beals smoothing, diversity analysis such as rarefaction curves, etc.)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• CRAWLEY, Michael J. The R book. Chichester: Wiley, 2007, viii, 942. ISBN 9780470510247. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized).

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2011

Extent and Intensity

1/1/0. 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)

Bi7540 Data anal. commun. ecology

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 11 fields of study the course is directly associated with, display

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2010

Extent and Intensity

1/1/0. 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)

Bi7540 Data anal. commun. ecology

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

Language of instruction

Czech

Further comments (probably available only in Czech)

Study Materials
The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

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

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology (both classes could be taken in one semester), but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.).

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, B-BI, specialization Systematic Zoology and Ecology)
• Systematic Biology and Ecology (programme PřF, N-BI, specialization Botany)
• Systematic Biology and Ecology (programme PřF, N-BI, specialization Zoology)

Course objectives

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Additional methods (e.g. Beals smoothing, diversity analysis such as rarefaction curves, etc.)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• CRAWLEY, Michael J. The R book. Chichester: Wiley, 2007, viii, 942. ISBN 9780470510247. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized).

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

Extent and Intensity

1/1/0. 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

Bi7540 Data anal. commun. ecology
The class is focused on the use of R for analysis of multivariate ecological data. It is meant to be a continuation of Bi7540 Data analysis in community ecology, but oriented more practically and limited purely on the use of R (I expect, at least partially, students to gain their theoretical knowledge in Bi7540 or other courses). Before signing for this course, student should have also elementary experience with R program operation (gained by self-study or by attending other classes, such as Bi7560 Introduction to R, Bi8190 Visualization of biological data, Bi7920 Analysis of biological data etc.).

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

At the end of the class, students should be able to analyze various types of ecological data using the R program. The class should also provide an inspiration for further individual improvements in using R program. R is not only substitution for PC-ORD or CANOCO - it offers much more, from almost unlimited selection of various statistical approaches up to the creative freedom, allowing one to handle any type of analysis and data.

Syllabus

• 1. Introduction, basic data operations, libraries vegan and labdsv, recommended references 2. Betadiversity, similarity matrices, Mantel's test 3. Numerical classification methods 4. Unconstrained ordination 5. Constrained ordination 6. Classification and regression trees 7. Additional methods (e.g. Beals smoothing, diversity analysis such as rarefaction curves, etc.)

Literature

• Oksanen J. (2010): Multivariate analysis of ecological communities in R: vegan tutorial. URL: http://cc.oulu.fi/~jarioksa/opetus/metodi/vegantutor.pdf
• Roberts, D.V. (2009): R labs for vegetation ecologists. URL: http://ecology.msu.montana.edu/labdsv/R/
• CRAWLEY, Michael J. The R book. Chichester: Wiley, 2007, viii, 942. ISBN 9780470510247. info

Teaching methods

Lessons will combine theoretical parts, focused on theoretical background of particular methods, and practical parts, in which these methods will be applied on real datasets (practical part will be emphasized).

Assessment methods

Students will elaborate a final thesis, analysing their own (or borrowed) data using some of the methods tought in the class. Class will be concluded by oral examination, which will have form of discussion about the thesis with additional questions. During the class, student will elaborate several voluntary homeworks for training of selected methods.

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

The course is not taught in Autumn 2011 - acreditation

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

Extent and Intensity

1/1/0. 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)

Bi7540 Data anal. commun. ecology

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

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

Bi7550 Analysis of community ecology data in R program

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

Extent and Intensity

1/1/0. 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)

Bi7540 Data anal. commun. ecology

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

Language of instruction

Czech

Further comments (probably available only in Czech)

The course can also be completed outside the examination period.
The course is taught once in two years.
Information on the per-term frequency of the course: jaro 2011, 2013, ...
The course is taught: every other week.

• Enrolment Statistics (recent)