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401-3622-00L 8 Credits BSC , MSC , WBZ D-ITET , D-MATH , D-INFK
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Statistical Modelling

Lecturers & Examiners: Prof. Dr. Peter L. Bühlmann
VVZ CR 4.6

Last Updated: 2026-02-05 16:02:00

Abstract

In regression, the dependency of a random response variable on other variables is examined. We consider the theory of linear regression with one or more covariates, high-dimensional linear models, nonlinear models and generalized linear models, robust methods, model choice and nonparametric models. Several numerical examples will illustrate the theory.

Objective

Introduction into theory and practice of a broad and popular area of statistics, from a modern viewpoint.

Content

In der Regression wird die Abhängigkeit einer beobachteten quantitativen Grösse von einer oder mehreren anderen (unter Berücksichtigung zufälliger Fehler) untersucht. Themen der Vorlesung sind: Einfache und multiple Regression, Theorie allgemeiner linearer Modelle, Hoch-dimensionale Modelle, Ausblick auf nichtlineare Modelle. Querverbindungen zur Varianzanalyse, Modellsuche, Residuenanalyse; Einblicke in Robuste Regression. Durchrechnung und Diskussion von Anwendungsbeispielen.

Resources

Learning Materials (Links)

General Information

Language
English
Levels
BSC , MSC , WBZ
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 120 minutes
Aids
One sheet of paper (A4, front and back) with a machine- or handwritten summary; a non-programmable pocket calculator
Digital
The exam takes place on devices provided by ETH Zurich.
Credits cannot be recognised for both courses 401-3622-00L Statistical Modelling and 401-0649-00L Applied Statistical Regression in the Mathematics Bachelor and Master programmes (to be precise: one course in the Bachelor and the other course in the Master is also forbidden).

Course Components

Type Title Time & Place Hours
lecture with exercise Statistical Modelling
  • Mon 10:15-12:00 (ML D 28)
  • Thu 14:15-16:00 (HG E 1.1)
4 h weekly

Offered In