Course

Generalized Linear Models (STA600)

Introduction to glm, which is a generalization of (multiple) regression for normally distributed responses to responses from a larger class of distributions, especially discrete responses. Theory for glmÂ’s with application to regression for normally distributed data, logistic regression for binary and multinomial data; Poisson regression and survival analysis. Applications to data, principles of statistical modeling, estimation and inference are emphasized. Likelihood theory.


Dette er emnebeskrivelsen for studieåret 2025-2026

Fakta

Emnekode

STA600

Vekting (stp)

10

Semester undervisningsstart

Spring

Undervisningsspråk

English

Antall semestre

1

Vurderingssemester

Spring

Content

NB! This is an elective course and may be cancelled if fewer than 10 students are enrolled by January 20th for the spring semester.

Introduction to generalized linear models (GLM), which is a generalization of (multiple) regression for normally distributed responses to responses from a larger class of distributions, especially discrete responses. Theory for GLMs with application to among other tings, regression for normally distributed data, logistic regression for binary and multinomial data; Poisson regression and survival analysis. Principles of statistical modeling, likelihood theory, estimation and inference, bayesian methods. Applications and analyses of data sets are emphasized.

Learning outcome

After having completed the course one the student should:

  • Know the main theory for generalized linear models
  • Know how regression with binary, multinomial, Poisson- and survival time responses may be done
  • Understand use of likelihood estimation generally and especially for generalized linear models
  • Be able to apply the theory in practical use on real data.

Forkunnskapskrav

Et av følgende alternativer:
Mathematical Methods 1 (MAT100)
Mathematical Methods 2 (MAT200)
Probability and Statistics 1 (STA100)
Probability and Statistics 2 (STA500)
or equivalent courses.

Anbefalte forkunnskaper

Probability and Statistics 2 (STA500)

Exam

Form of assessment Weight Duration Marks Aid
Oral exam 1/1 45 Minutes Letter grades None permitted


Oral exam is individual.

Vilkår for å gå opp til eksamen/vurdering

Two compulsory assigned exercises
Mandatory assignments must be passed for the student to have admittance to the exam.

Fagperson(er)

Head of Department:

Bjørn Henrik Auestad

Course coordinator:

Arild Buland

Course coordinator:

Tore Selland Kleppe

Course coordinator:

Jörn Schulz

Method of work

4 hours lectures and 2 hours problem solving per week.

Åpent for

Mathematics and Physics - Bachelor's Degree Programme City and Regional Planning - Master of Science Computational Engineering - Master of Science Degree Programme Computer Science - Master of Science Degree Programme Environmental Engineering - Master of Science Degree Programme Industrial Economics - Master of Science Degree Programme Robot Technology and Signal Processing - Master's Degree Programme Structural and Mechanical Engineering - Master of Science Degree Programme Mathematics and Physics - Master of Science Degree Programme Mathematics and Physics - Five Year Integrated Master's Degree Programme Offshore Field Development Technology - Master of Science Degree Programme Industrial Asset Management - Master of Science Degree Programme Marine and Offshore Technology - Master of Science Degree Programme Offshore Technology - Master's Degree Programme Petroleum Geosciences Engineering - Master of Science Degree Programme Petroleum Engineering - Master of Science Degree Programme Master's Degree Programme in Societal Safety, Specialisation in Technical Social Safety Risk Management - Master's Degree Programme (Master i teknologi/siviling.)

Emneevaluering

There must be an early dialogue between the course supervisor, the student union representative and the students. The purpose is feedback from the students for changes and adjustments in the course for the current semester.In addition, a digital course evaluation must be carried out at least every three years. Its purpose is to gather the students experiences with the course.
The course description is retrieved from FS (Felles studentsystem). Version 1