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Session 3L. Multivariate Statistics

Session Organizer(s)

John Harraway (New Zealand) jharraway@maths.otago.ac.nz

Session Abstract

Multivariate statistical procedures form a key component of an undergraduate programme in statistics. But they are frequently taught as part of a graduate programme for researchers and postgraduate students in a wide range of non-mathematical disciplines where the collection and analysis of data are important. These courses are enjoyable and students have even been heard to comment that their course on multivariate methods has been the most useful course they have attended. The material is often taught with a practical emphasis rather than from a theoretical perspective, it covers the use and comparisons of several statistical packages, investigates the choice of correct models for particular types of data, and establishes a range of valid and rigorous tests without mathematical detail, frequently for data that are not multivariate normal.

As well as discussing some of the more recently developed multivariate techniques, this session will include a series of papers highlighting the breadth of application by covering methodology and data from such diverse areas as epidemiology, ecology, environmental science, marketing research and the social sciences. For each of these subjects, interesting recent data sets will be presented which participants in the session will be able to access and use to enhance their own teaching. Longitudinal data from HIV/AIDS programme evaluation will be considered, examples from marketing research using some of the newer multivariate techniques will be presented, and the use of distance functions in ecology will be investigated.

Presentations

Presentation 3L1 Multivariate Methods for Ecology and Environmental Science Marti J. Anderson (NZ)
Presentation 3L2 Hierarchical Linear Models for the Analysis of Longitudinal Data with Applications from HIV/AIDS Program Evaluation Ann A. O'Connell (USA)
Presentation 3L3 Making Multivariate Interesting and Fun For Students Joe F. Hair, Jr. (USA)

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