Applied Multivariate Analysis

About

The emphasis is on applying multivariate techniques using SPSS or R and on how to interpret the output in substantive terms.

Many research questions in the social and behavioural sciences are investigated using statistical models. We offer a crash course in applied multivariate analysis in which we focus on simple and factorial ANOVA, interaction effects, repeated measures ANOVA, ANCOVA, MANOVA, MANCOVA, multiple linear regression analysis (including the use of dummy variables), logistic regression analysis, and principal component analysis.

In this course the emphasis is on applying multivariate techniques using SPSS or R, and on how to interpret the output in substantive terms. Mathematical details are not discussed.

Participants need to bring their own laptop. Software will be available online.

Course leader

Dr. David Hessen

Target group

Students with a BSc in Social and Behavioural Sciences who have introductory knowledge of statistics. Students should be familiar with the following concepts: null hypothesis, alternative hypothesis, population, sample, statistical significance, practical and theoretical significance, correlation, regression, and t-test . Some experience with SPSS or R is advisable. A maximum of 48 participants will be allowed to participate in this course.

There are no restrictions on who can participate beyond the prerequisites; academics, researchers, and professional participants are all welcome to register for the course.

For an overview of all our summer courses offered by the Department of Methodology and Statistics please click here.

We also offer tailor-made M&S courses and in-house M&S training. If you want to look at the possibilities, please contact Dr. Laurence Frank at pe.dsai@uu.nl.

Course aim

This course offers hands-on experience using SPSS or R for the most frequently encountered multivariate statistical techniques in the social and behavioural sciences.

Learning goals:
- Selection of appropriate statistical procedures
- Execution of statistical procedures using SPSS or R
- Interpretation of SPSS or R output

Fee info