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Statistics for Experimental Research
Last Updated: 2026-02-05 16:08:44
Abstract
Students will learn the necessary statistical concepts and skills to independently (1) design experiments (2) analyse experimental data and (3) report analyses and results in a scientifically appropriate manner.
Objective
After successful completion of the course, students should be able to: 1. Determine appropriate experimental designs and choose, justify and perform the appropriate statistical analyses using R. 2. Report analyses and results in a scientifically appropriate manner, as laid out by the Publication Manual of the American Psychological Association (APA, sixth edition).
Content
We will cover basic statistical concepts (e.g., central tendency, variability, data distribution), the t-test (dependent and independent), ANOVA (univariate, factorial and repeated measures), correlation, multiple regression, nonparametric techniques, validity and reliability tests, effect size, data transformation, power and sample size estimation.
Resources
Lecture Notes
Lecture notes will be delivered in the form of commented presentations in Microsoft Powerpoint (i.e. pptx) format. R practical session assignments will be delivered in pdf-format.
Literature
Both in the lectures and in the tutorials and practical sessions, we will refer students to the following publication: Field A, Miles J, Field Z (2013) Discovering Statistics Using R. Sage Publications Ltd, London, UK
Learning Materials (Links)
- Main link
- Stats 2022 Moodle Course
General Information
- Language
- English
- Levels
- DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Statistics for Experimental Research |
|
2 h weekly |
Offered In
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