Kies de Nederlandse taal
Course module: 822187-B-6
Statistics for CSAI 1
Course info
Course module822187-B-6
Credits (ECTS)6
CategoryBA (Bachelor)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Humanities and Digital Sciences; TSH: Department Cognitive Science and AI; TSH: Department Cognitive Science and AI;
Is part of
B Communication and Information Sciences
B Communication and Information Sciences (Spc.Cog.Sc & AI)
B Cognitive Science and Artificial Intelligence
Contact personT.J. Wiltshire
E. Fukuda
Other course modules lecturer
Coordinator course
dr. M. Postma
Other course modules lecturer
dr. M. Postma
Other course modules lecturer
T.J. Wiltshire
Other course modules lecturer
Academic year2018
Starting block
SM 1/  SM 2
Course mode
RemarksThis information is not up to date. Check the Course Catalog 2019 or select the course via “Register”.
Registration openfrom 20/08/2018 09:00 up to and including 31/07/2019
Please Mind: the complete information for this course is not provided yet, this page will be finalized in the upcoming weeks

• Demonstrate competence with the basics of the statistical programming language R including, but not limited to, loading and transforming data, finding and installing packages,     applying functions, and working with scripts
• Create effective visualizations of data using R
• Use and interpret descriptive statistics to understand data using R
• Conduct and interpret means comparison-based analyses such as t-tests and analysis of variance using R
• Conduct and interpret output from non-parametric analyses using R

This course is primarily assessed using individual midterm and final exams that are administered in person, which are each worth 50% of your final grade. Both the midterm and the final exam consist of multiple choice questions. Students need to pass both the midterm and the final exam to pass the course. In addition, students will be asked to submit 5 practical exercises. The exercises are not graded, but students will be expected to submit them and to provide a self-evaluation based on provided answers. 
Students have to take part in "proefpersoonuren" for 10 hours. These hours can be completed by participating in human experiments (check out and by participating in computational studies and hackathons announced by the study program director throughout the course of the academic year. For human experiments, students can enrol via this link for research: 
This course involves a combination of lecture, demonstration, and practical exercises designed to introduce students to the basics of both the statistical programming language R as well statistics. We will use RStudio, which makes it more efficient to work with R. We utilize R as it a powerful and scalable tool for working with and analyzing any type of data, and it’s free and open source.

The topics in the course include the basics of the R statistical programming language and navigating the RStudio environment, creating different visualizations of data, understanding and utilizing functions that provide descriptive statistics about data, as well when and how to applying different inferential statistics including t-tests, analysis of variance, and non-parametric tests. 
Timetable information
822187-B-6|Statistics for CSAI 1
Written test opportunities
Written test opportunities (HIST)
Midterm / MidtermMIDTERM_01SM 1115-10-2018
Schriftelijk / WrittenEXAM_01SM 1119-12-2018
Schriftelijk / WrittenEXAM_01SM 1223-01-2019
Midterm / MidtermMIDTERM_01SM 1223-01-2019
Midterm / MidtermMIDTERM_01SM 2127-03-2019
Schriftelijk / WrittenEXAM_01SM 2103-06-2019
Midterm / MidtermMIDTERM_01SM 2224-06-2019
Schriftelijk / WrittenEXAM_01SM 2201-07-2019
Required materials
Selected chapters from Navarro, D. (2015). Learning statistics with R. Retrievable from
Title:Learning statistics with R
Author:D. Navarro
Publisher:Retrievable from
Recommended materials
Title:Discovering Statistics
Author:Field, A., Miles, J., & Field, Z


Final Grade

Kies de Nederlandse taal