Multivariate Statistik

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Organization

When and where

The following table contains the provisional terms and locations of the course.

Terms	Location
Tuesday 12:30-14:00	SR C208
Thursday 9:00-11:00	SR Inst. f. Stat. (407)
Subscription Number	Hours/Week
506.068,506.069	2+1

Lecturer

For questions contact

Stampfer Erwin

Institute of Statistics

stampfer@stat.tu-graz.ac.at

Course description

Basics of Multivariate Statistics, Multivariate Normal Distribution, Discriminance Analysis, Principal Components, Clustering.

Aims and objectives of the course

Presentation of fundamental concepts of modern Multivariate Analysis. Solving practical problems with suitable software.

Teaching method

The theoretical concepts, presented in the lectures, will be applied to data. The software package SPLUS will be utilized.
Prerequisite: Probability Theory and Mathematical Statistics.

Teaching aids

Johnson, R. A., Wichern D. W. (1982): Applied Multivariate Statistical Analysis. Prentice Hall.
Mardia, K.V., Kent, J.T. and Bibby, J.M.(1979): Multivariate Analysis.
Flury, B. (1997): A first course in Multivariate Statistics. Sringer.

Examination Method

Short presentations during the course. Oral examination at the end.

Zurück.

We will look at different data sets. The first one, which will be used for motivation of different multivariate topics is the swiss banknote dataset. (Taken from Riedwyl, H., University Bern.) Second one is a nice example for a mixture distribution with unknown component membership.

The swiss banknote dataset: SBN-Text , SBN-SPSS , SBN-SAS , SBN-Definition ,
The wing length data: SBN-Text , SBN-SPSS , SBN-SAS , SBN-Definition ,