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401-0649-00L 5 Credits BSC , DR , MSC , WBZ , NDS D-HEST , D-MATH , D-BIOL , D-INFK , D-ERDW , D-BAUG , D-ITET , D-USYS

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Applied Statistical Regression

Lecturers & Examiners: Dr. Marcel Dettling

VVZ CR n/a

Last Updated: 2026-02-05 15:48:56

Abstract

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.

Objective

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

Content

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.

Resources

Lecture Notes

A script will be available.

Literature

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

General Information

Language: English
Levels: BSC , DR , MSC , WBZ , NDS
Frequency: Yearly recurring

Examination

Type: session examination
Mode: written 120 minutes
Aids: Open book, i.e. any written material is allowed. We recommend to bring a pocket calculator.

Exam questions may be answered in English or in German.Mathematics Bachelor / Mathematics Master: see notice in the catalogue data.

Course Components

Type	Title	Time & Place	Hours
lecture	Applied Statistical Regression	Mon 08:15-10:00 (HG E 1.2)	2 h weekly
exercise	Applied Statistical Regression Mon 10-12 might not work for all different programmes where this course is offered. On sufficient demand, other slots (tentatively Mon 15-17 or Fri 10-12) for the exercise sessions can be offered.	Mon 10:15-12:00 (HG E 1.2)	1 h weekly

Offered In

Mathematics Bachelor
- Electives
  - Selection: Probability Theory, Statistics
Earth and Climate Sciences Bachelor
- Majors
  - Major: Climate and Water (Advisor of the BSc-major "Climate and Water" is Dr. Hanna Joos, Institute for climate and atmosphere (IAC).)
    - Electives (The electives listed are recommended. Additional courses can be chosen from the complete offerings of the ETH Zurich and University of Zurich.)
Environmental Sciences Bachelor (Students can choose between one Bachelor thesis of 10KP or two Bachelor theses of 5KP each. In principle, all professors and lecturers involved in the teaching of the Environmental Sciences degree programme are entitled to supervise a Bachelor's thesis (BA). BA in the area of social sciences and humanities can only be supervised by lecturers who teach in this area. The same applies to BA in the field of natural sciences and technology. If the thesis is supervised by a person who does not teach in the Environmental Sciences degree programme or who does not have ETH lecturer status, then the student has to fill in the "Form for supervisors of a Bachelor thesis who do not teach in the Environmental Sciences degree programme" Link)
- Natural Science and Technical Electives
  - Methodes of Statistical Data Analysis
Mathematics Master
- Electives (For the Master's degree in Applied Mathematics the following additional condition (not manifest in myStudies) must be obeyed: At least 15 of the required 28 credits from core courses and electives must be acquired in areas of applied mathematics and further application-oriented fields.)
  - Electives: Applied Mathematics and Further Application-Oriented Fields (¬)
    - Selection: Probability Theory, Statistics
Biology Master
- Elective Major Subject Areas
Food Science Master
Biology (General Courses)
- Complementary Courses
Statistics Master (The following courses belong to the curriculum of the Master's Programme in Statistics. The corresponding credits do not count as external credits even for course units where an enrolment at ETH Zurich is not possible.)
- Master Studies (Programme Regulations 2014)
  - Core Courses (In each subject area, the core courses offered are normally mathematical as well as application-oriented in content. For each subject area, only one of these is recognised for the Master degree.)
    - Regression
MAS in Sustainable Water Resources (The Master of Advanced Studies in Sustainable Water Resources is a 12 month full time postgraduate diploma programme. The focus of the programme is on issues of sustainability and water resources in Latin America, with special attention given to the impacts of development and climate change on water resources. The programme combines multidisciplinary coursework with high level research. Sample research topics include: water quality, water quantity, water for agriculture, water for the environment, adaptation to climate change, and integrated water resource management. Language: English. Credit hours: 66 ECTS. For further information please visit: )
- Elective Courses (Electives: 6 credits has to be achieved.)
Doctoral Department Biology (More Information at: )
- Doctoral and Post-Doctoral Courses
DAS in Data Science
- Specialisation Track
  - Statistics