MAT3236

Applied statistics 3

Coordinators: Assoc Prof P R Rayment and Dr H B Nath

8 points - First semester - Four hours of lectures and one 1-hour tutorial/ computing workshop per week - Gippsland and distance - Prerequisites: MAT2236 Applied Statistics 2 - Prohibitions: MAT2762, MAT3762, MAT2763, MAT3763, MAT2781, MAT3752, MAT3782

Objectives The objectives of the subject MAT3236 are for students to (1) become critical users of a range of modern methods of univariate and multivariate analysis which are widely used in the analysis of data in the environmental, biomedical and other fields; (2) be able to formulate statistical models for a range of archetypal investigations/experiments; (3) demonstrate an understanding of the assumptions required for valid application of the methods identified in (1); (4) effectively utilise appropriate statistical software to implement the analyses; (5) correctly interpret the computer-generated results of the analyses.

Synopsis Section A. Further topics in design and analysis of experiments, building on subject MAT2236 (Applied statistics 2): power analysis for analysis of variance (ANOVA); fixed, random and mixed models for ANOVA; nested designs; analysis of repeated measures experiments including growth curve analysis. Section B. Modern methods of biostatistical analysis: introduction to multivariate data analysis techniques - graphical display of multivariate data, representation and condensation of multivariate data, Hotelling's T-squared test; dicriminant analysis; principal components and their use in data condensation; analysis of contingency tables and log-linear models; logistic regression analysis and its relationship to log-linear models; introduction to survival data analysis.

Assessment Assignments (three): 10% each - Examination (three hours): 70%)

Prescribed texts

Selvin S Practical biostatistical methods Duxbury Press, 1995
Manly B F J Multivariate statistical methods - a primer 2nd edn, Chapman and Hall, 1994

Back to the 1999 Science Handbook