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401-8623-00L 7 Credits MSC D-MATH
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Likelihood and Regression I (University of Zurich)

No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH as an incoming student. UZH Module Code: STA402 Mind the enrolment deadlines at UZH:
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Last Updated: 2026-02-05 16:29:34

Abstract

Overview over the basics of statistical inference.Introduction to modern regression methods.

Content

First part of the semester: Overview over the basics of statistical inference. Topics include the introduction to the concept of likelihood and the discussion of likelihood functions of a large variety of statistical models, sufficiency and the likelihood principle, properties of maximum likelihood estimates, standard errors, confidence intervals and pivots, score function and Fisher information, Cramer-Rao bound, confidence intervals and significance tests based on the Wald, score and likelihood ratio statistic, variance-stabilizing transformations, treatment of nuisance parameters, conditional and profile likelihood. The lecture also covers the very basic ideas of Bayesian statistics. Second part of the semester: Introduction to modern regression methods. After a brief recap of classical regression techniques the following topics will be discussed: exponential family of distributions and generalized linear models (GLM), estimation and inference for GLMs, likelihood ratio and deviance, normal linear models, Categorical data and logistic regression, Poisson regression and log-linear models. If time allows we might also discuss mixed effects models, nonparametric regression and additive models.

Resources

Literature

Fahrmeir, L., Kneib, T. and Lang, S. (2013) Regression: Models, Methods and Applications Tutz, G. (2012). Regression for Categorical Data

General Information

Language
English
Levels
MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
Registration modalities, date and venue of this performance assessment are specified solely by the UZH.

Course Components

Type Title Time & Place Hours
lecture with exercise Likelihood and Regression I (University of Zurich)
**Course at University of Zurich** This is the new Module that consists of the old half semester Modules STA402 Likelihood Inference and STA406 Generalized Regression. Students who already passed the old STA402 cannot book STA402. Students who failed the old STA402 twice can still take STA402.
  • Wed 08:00-09:45
  • Wed None-None
  • Wed None-None
  • Wed 11:15-13:45
  • Wed None-None
  • Wed None-None
4 h weekly

Offered In

  • 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.)
    • Core Courses
      • Mathematical Statistics (The three core courses Fundamentals of Mathematical Statistics (401-3621-00L) and Likelihood and Regression Part 1 (401-8623-01L) and the latter's former version Likelihood Inference (401-8623-00L) are similar in content. Therefore only one of them can be recognised towards the Master’s degree in the core course area «Mathematical Statistics».)