Explanatory Data Analysis group

Statistics

Prospectus
21-22, 20-21, 19-20, 18-19, 17-18, 16-17
Level
BSc, 6 EC
Part of
BSc Data Science & Artificial Intelligence, BSc Computer Science, minor Data Science
Language
Dutch
Lecturers
Matthijs van Leeuwen, Marieke Vinkenoog
Assistants
Hermes Spaink, Lincen Yang, Chris Congleton, Job van Dijke, Michael de Rooij, 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:

  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

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).