Explanatory Data Analysis group


20-21, 19-20, 18-19, 17-18, 16-17
BSc, 6 EC
Part of
Artificial Intelligence, Computer Science, Computer Science & Economy, Bioinformatics, minor Data Science
Matthijs van Leeuwen, Iris Yocarini
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.

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:

  1. Introduction
  2. Data and probability
  3. Descriptive statistics
  4. Random variables and probability distributions
  5. Estimation
  6. Discussion on 1st assignment, expectation
  7. Hypothesis testing
  8. Comparing two groups
  9. Assocations between categorical variables
  10. Regression and correlation
  11. Multiple regression and correlation
  12. Analyse the analysis, Q&A
  13. Statistical learning

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).