Applied Statistical Regression

Autumn semester 2021

General information

Lecturer Marcel Dettling
Assistant Meta-Lina Spohn
Lectures Mon 08-10 HG E 1.2 >> and/or via zoom
Exercises Mon 10-12 (bi-weekly) HG E 1.2 >> and/or via zoom
Course catalogue data >>

Faraway (2005): Linear Models with R
Faraway (2006): Extending the Linear Model with R
Draper & Smith (1998): Applied Regression Analysis
Fox (2008): Applied Regression Analysis and GLMs
Montgomery et al. (2006): Introduction to Linear Regression Analysis

Course content


This course offers a practically oriented introduction into regression modeling methods. The basic concepts and some mathematical background are included, with the emphasis lying in learning "good practice" that can be applied in every student's own projects and daily work life. A special focus will be laid in the use of the statistical software package R for regression analysis.


The students acquire advanced practical skills in linear regression analysis and are also familiar with its extensions to generalized linear modeling.


The course starts with the basics of linear modeling, and then proceeds to parameter estimation, tests, confidence intervals, residual analysis, model choice, and prediction. More rarely touched but practically relevant topics that will be covered include variable transformations, multicollinearity problems and model interpretation, as well as general modeling strategies.

The last third of the course is dedicated to an introduction to generalized linear models: this includes the generalized additive model, logistic regression for binary response variables, binomial regression for grouped data and Poisson regression for count data.


The exercises, but also the classes will be based on procedures from the freely available, open-source statistical software package R, for which an introduction will be held.


  • August 20st, 2021:
    Beginning of lecture and exercise class: Monday, 27.09.2021.

Course materials

All course material will be provided on the Moodle-course webpage.

Exercise classes

Exercises will be held roughly bi-weekly, see below. On these dates, the exercise classes will take place from 10:15 to 11:55 in HG E 1.2 (or via zoom, still to be decided). The first exercise class is meant to be an opportunity for you to ask questions regarding the software R. The material you should be familiar with consists of the R tutorial and exercise sheet 1. Also further on, R will be used during the exercises so that you are expected to bring your laptop to the classes. Starting with the second exercise class, the idea is that there will be a discussion of the old exercise sheet (common problems) and a discussion of the new exercise sheet (hints and theory as needed) taking at most one hour. Afterwards, you work on the problems using the computer; the assistants will be there to give instructions and support.

The dates of the exercise classes are the following:
  • September 27, 2021
  • October 11, 2021
  • October 25, 2021
  • November 08, 2021
  • November 22, 2021
  • December 06, 2021
  • December 20, 2021
Exercise sheets (Series) and corresponding Solutions will be uploaded to the Moodle-course webpage. The Series will be uploaded one week previous to the exercise class, and the Solution one week after the exercise class. PhD students who want to receive ETH credits, need to hand-in at least 5 out of the Series 2-8 via mail to Meta-Lina Spohn. The hand-in is due on the dates indicated on Moodle till 11.00 am. The Solutions are uploaded after this. Students who take the exam in the end do not need to hand-in any Series.

Help with R

During the first exercise class you will have the opportunity to ask questions regarding the software R. Further material can be found following the links below.

R homepage
R studio homepage
Getting help with R
Online R course (in German)
Try R