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.
Learning 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.
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
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits
3 credits
Examiners
Type
graded semester performance
Language of examination
English
Repetition
Repetition possible without re-enrolling for the course unit.
Performance assessment as a semester course