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Generalized linear models, spring 2010

Lecturer

dos. Juha Karvanen

Scope

6 cu + optional practical work (harjoitustyö) of 2 cu.

Harjoitustehtävät, tentin ja harjoitustyön voi tehdä myös suomeksi. Kysymykset ovat englanniksi mutta vastaukset voi antaa suomeksi.

Type

Advanced studies.

Prerequisites

Generalized linear models are an extension of the usual linear model, where the response variable may be discrete or have a skew distribution. The course covers the generic likelihood-based estimation and test theory of generalized linear models. The most important special cases, like logistic and log-linear models, are treated in more detail.

The course will be a balanced mixture of statistical theory and practical data analysis. R (http://www.r-project.org) is used for data analysis and simulations. Examples from application areas, such as epidemiology and physics, will be presented.

Prerequisites

  • Basics concepts of
    • mathematical analysis (derivatives and integrals)
    • matrix algebra (up to multiplication and inversion of matrices)
    • probability (random variables, standard distributions, expectation, variance, independence)
    • statistical inference (maximum likelihood, hypothesis testing).
  • Knowledge of linear models is also useful.

Course material

Lectures

Period IV

Wednesdays, starting from 24. March, 14-18 in: 

24. March, 14., 21., 28. April, 5., 12. May  in Unioninkatu 40, U40 Class 6

31. March in University main building, Class 15

Easter holiday 1.-7.4.

Exams

The time of the course exam has changed

24 May 2010, 16-18 C323

24 May 2010, 16-18 C323
10 June 2010, 10-12 Summer exam (register by 31 May)

Bibliography

  • McCullagh, P. & Nelder, J.A. Generalized linear models, 2nd edn, Chapman & Hall, 1989.
  • Course material

Registration

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Exercises

Starting

Day

Time

Place

Instructor

29.3.2010

Mon

16-18

Kumpula, Exactum, C323

Olli Saarela

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