#### Explanatory Data Analysis group

### Statistics

- Prospectus
- 20-21, 19-20, 18-19, 17-18, 16-17
- Level
- BSc, 6 EC
- Part of
- Artificial Intelligence, Computer Science, Computer Science & Economy, Bioinformatics, minor Data Science
- Language
- Dutch
- Lecturers
- Matthijs van Leeuwen, Iris Yocarini
- Assistants
- Marieke Vinkenoog, Lincen Yang, Sophie van der Bliek, Anne Liebens, Milou Schamhart
- For students
- All material, including slides and exercises, and announcements will be communicated through Brightspace.
- Contents
In this course, primarily aimed at Computer Science students, we cover the basics of statistics, the fundamental 'data science' that researches the description and analysis of data. The focus is on learning how to correctly apply statistical methods, not on their mathematical justification.

The following provides a high-level overview of the lectures of the course:

- Introduction
- Data and probability
- Descriptive statistics
- Random variables and probability distributions
- Estimation
- Discussion on 1st assignment, expectation
- Hypothesis testing
- Comparing two groups
- Assocations between categorical variables
- Regression and correlation
- Multiple regression and correlation
- Analyse the analysis, Q&A
- Statistical learning

- Literature
- Statistical Methods for the Social Sciences, Alan Agresti, Global Edition – Fifth Edition, Pearson Education, ISBN 9781292220314 (
*hardcopy is mandatory, e.g., for use during open book exam*).