Instructors
Gabriel Singer, Lauren Talluto, Thomas FußThis course covers various univariate and multivariate statistical analyses appropriate for common applied problems in ecology. We discuss the theoretical foundations of the analyses, assumptions, applications. We also introduce data preparation and visualisation. Via worked examples, students learn to perform analyses in R, as well as in Canoco (for some multivariate analyses).
Following the course, students should be able to:
- Describe common univariate statistical tests, including the hypotheses tested and assumptions required.
- Implement tests in R, including reading and preparing data.
- Interpret the output of tests, draw conclusions in terms of the ecological hypotheses being tested, and describe the results in plain language.
- Use visualisation tools in R for exploratory analysis and final presentation.
- Decide when the structure of the data requires multivariate analysis, and choose an appropriate method.
- Apply multivariate statistics in R.
- Interpret (with the help of visualisation) multivariate analyses in terms of the original variables.
Students will be graded based on their participation during the exercise sessions (40%) and on completion of three protocols (one per unit, 20% each, total of 60%). These protocols can be completed individually or in small groups (max. 3 students per group) and will be due on 14 February 2025. Details about the assignments and expectations will be provided on the first day of class.
Note that attendence is mandatory.
You can get student files for the course, as well as instructions for setting up your workspace, at the student github repository
| Topics | Exercises (in-class) | Protocol | ||
|---|---|---|---|---|
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Unit 1 Talluto |
Day 1
G0: 13.01 14:30–18:45, RR18 G1: 16.01 8:00–11:45, RR18 |
Introduction to R Populations, samples Descriptive statistics |
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Day 2
G0: 14.01 8:00–11:45, RR20 G1: 17.01 12:00–15:15, RR18 |
Confidence intervals Significance tests Type I and II errors |
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Day 3
G0: 15.01 8:00–11:45, RR18 G1: 20.01 13:45–18:30, RR18 |
Data structures Visualisation Association and Correlation |
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Unit 2 Singer |
Day 4
G0: 22.01 13:45–17:30, RR18 G1: 23.01 8:00–11:45, RR18 |
Linear regression |
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Day 5
G0: 23.01 13:45–18:00, RR18 G1: 24.01 14:30–18:45, RR19 |
Multiple linear regression Model selection |
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Day 6
G0: 24.01 8:00–11:45, SRB G1: 27.01 8:00–11:45, RR18 |
ANOVA ANCOVA Nonparametric location tests |
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Unit 3 Fuß |
Day 7
G0: 27.01 9:00–13:15, SRB G1: 29.01 13:00–17:15, RR21 |
Principle components analysis (PCA) Redundancy analysis (RDA) |
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Day 8
G0: 28.01 8:00–11:45, RR20 G1: 30.01 8:00–11:45, RR18 |
RDA continued Permutation tests |
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Day 9
G0: 29.01 8:00–11:45, RR21 G1: 31.01 8:00–11:45, RR18 |
Nonmetric multidimensional scaling (NMDS) |
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Meeting locations Rechneraum 18, Architekturgebäude UG (RR18) Rechneraum 19, Architekturgebäude UG (RR19) Rechneraum 20, Architekturgebäude UG (RR20) Rechneraum 21, Architekturgebäude UG (RR21) Seminarraum Biologie, EG, Technikerstr. 25 (SRB) |
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