t.BA.XX.STMO.20HS (Statistical Modelling) 
Module: Statistical Modelling
This information was generated on: 24 July 2024
Statistical Modelling
Organised by


Version: 2.0 start 01 February 2021

Short description

The module introduces students to the basics of statistical modelling using linear regression analysis. Aspects of the model structure, inference, prediction, residuals analysis and model building, including variable selection, are examined in detail, both theoretically and in case studies.

Module coordinator

Ruckstuhl, Andreas (rkst)

Learning objectives (competencies)

Objectives Competences Taxonomy levels
You are familiar with practice-relevant methods of simple and multiple linear regression analysis and are able to interpret corresponding results F, M K3, K4
You can recognize from which principles the methods are derived F, M K2
You can assess whether the regression model fits the data F, M K3, K4, K6
You can develop a regression model using data F, M K3, K4, K5
You can apply the methods covered practically with a statistics program package. F, M K3

Module contents

imple and multiple regression models, estimations (incl. principle of maximum likelihood and robust methods), parameter tests, confidence and prediction intervals, model adequacy checking (residual analysis), model comparison, variable selection (incl. information criterion of Akaike), model building, smoothing (local regression, smoothing spline), additive models.

Statistics program package R: Statistics and graphics routines for the treated methods.

Teaching materials

Lecture notes, tutorial sheets, possibly other supplementary materials such as slides, handouts etc.

Supplementary literature

Montgomery, Peck and Vining (2012), Introduction to linear Regression Analysis, 5th Ed., Wiley Series in Probability and Statistics


You are familiar with the basic concepts of statistics (WAST3).

Teaching language

(X) German ( ) English

Part of International Profile

( ) Yes (X) No

Module structure

Type 2a
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025


Description Type Form Scope Grade Weighting
Graded assignments during teaching semester exam In writing max 60 min grading max 20%
End-of-semester exam exam In writing 90 min grading min 80%


Exam during the teaching period and its weighting is defined in the module agreement.

Legal basis

The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Course: Statistisches Modellieren - Vorlesung
Statistisches Modellieren - Vorlesung


  • No module description is available in the system for the cut-off date of 02 August 2099.