VU Datenanalyse

UIBK, Winter Semester 2024

Instructors

Gabriel Singer, Lauren Talluto, Thomas Fuß

Course description

This 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).

Learning objectives

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.

Assessment

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.

Student files

You can get student files for the course, as well as instructions for setting up your workspace, at the student github repository

Course Outline

		Topics	Exercises (in-class)	Protocol
Unit 1 Talluto	Day 1 G0: 13.01 14:30–18:45, RR18 G1: 16.01 8:00–11:45, RR18	The Basics Introduction to R Populations, samples Descriptive statistics	Exercises 1	Protocol 1
	Day 2 G0: 14.01 8:00–11:45, RR20 G1: 17.01 12:00–15:15, RR18	Univariate statistics Confidence intervals Significance tests Type I and II errors
	Day 3 G0: 15.01 8:00–11:45, RR18 G1: 20.01 13:45–18:30, RR18	The Basics part II Data structures Visualisation Association and Correlation
Unit 2 Singer	Day 4 G0: 22.01 13:45–17:30, RR18 G1: 23.01 8:00–11:45, RR18	Linear Models I Linear regression	Exercises 2.1	Protocol 2
	Day 5 G0: 23.01 13:45–18:00, RR18 G1: 24.01 14:30–18:45, RR19	Linear Models II Multiple linear regression Model selection	Exercises 2.2
	Day 6 G0: 24.01 8:00–11:45, SRB G1: 27.01 8:00–11:45, RR18	Analysis of Variance ANOVA ANCOVA Nonparametric location tests	Exercises 2.3
Unit 3 Fuß	Day 7 G0: 27.01 9:00–13:15, SRB G1: 29.01 13:00–17:15, RR21	Multivariate Stats I Principle components analysis (PCA) Redundancy analysis (RDA) Permutation tests	Exercises 3.1	Protocol 3
	Day 8 G0: 28.01 8:00–11:45, RR20 G1: 30.01 8:00–11:45, RR18
	Day 9 G0: 29.01 8:00–11:45, RR21 G1: 31.01 8:00–11:45, RR18	Multivariate Stats II Nonmetric multidimensional scaling (NMDS)	Exercises 3.2
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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