Statistical Models

2019-2020

Course Objective

The goals of this course are to get acquainted with some of the most
commonly used statistical models, to learn how to apply these models in
valid settings, and to understand the basic theory behind these models.

Course Content

Analysis of Variance, Generalized Linear Models, Non-linear Models, Time
Series.

Teaching Methods

Lectures and tutorials.

Method of Assessment

Assignments and examination.

Entry Requirements

Statistics course.

Literature

Lecture notes "Statistical Models" by M.C.M. de Gunst.

Target Audience

mBA, mBA-D, mMath

Additional Information

Students will use statistical package R (www.r-project.org) for data
analysis.

Recommended background knowledge

Linear Algebra, Probability Theory and Statistics. Statistical Data
Analysis (X_401029)

General Information

Course Code X_400418
Credits 6 EC
Period P1+2
Course Level 400
Language of Tuition English
Faculty Faculty of Science
Course Coordinator dr. E.N. Belitser
Examiner dr. E.N. Belitser
Teaching Staff dr. E.N. Belitser

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture
Target audiences

This course is also available as: