- Analysis of grouped or longitudinal data using linear mixed models
- Basic principles of statistics
- Categorical data analysis using logistic regression
- Graphics in R (FLAMES workshop)
- Introduction to Internet Questionnaires with QUALTRICS
- Introduction to JMP Pro 14 software
- Introduction to Stata
- Method in data collection
- Method in research design
- Method in scale construction
- Multiple linear regression and ANOVA
- Multivariate statistics
- R Workshop

This course gives a practical introduction to the use of multiple linear regression in the analysis of continuous outcomes.

In simple linear regression a continuous outcome (e.g. blood pressure, salary) is predicted using one variable by searching for the line that best fits the data. In multiple regression we extend this idea to the context where 2 or more predictors are used to predict the outcome. In case of a categorical predictor multiple regression is often referred to as ANOVA or ANCOVA.

Each lesson is a combination of theoretical introductions followed by hands-on exercises in the software package SPSS.

For this course, we offer the **possibility to take an exam**. For the PhD students in the faculties IOB and Applied Economics, this is a requirement to obtain a credits for these courses, but people from other faculties are allowed as well.

If you are interested in taking the exam, check the wants-to-take-exam-box in the registration form. Participating in the exam costs 10€, which is deduced automatically from your educational credit.

- Day 1 **(see remark below)
- Shorte recap on simple linear regression
- Dummy coding of categorical variables
- The multiple linear regression model

- Day 2
- Two-way ANOVA and ANCOVA
- Including higher order and interaction terms in a multiple linear regression model

- Day3
- Model building (forward, backward)
- Checking the model assumptions and troubleshooting if model assumptions are not met
- How to deal with problems like multicollinearity

** If you have followed StatUa's course on "Basic Principles of Statstics" in November 2015 or earlier, you have already been taught the contents of Day1. In this case, attending day 1 is optional.

Students should be familiar with the concepts and techniques that are taught in the course "Basic Principles of Statistics". In particular, simple linear regression and one-way ANOVA are assumed to be known.