Statistical inference
Not offered in 1995
BS BT DT BC BP BDT
Associate Professor Philip Rayment
6 points * Second semester * 4 hours of integrated lectures/tutorials per week * Gippsland/Distance (even-numbered years only) * Prerequisites: GAS2613, GAS2631, GAS3631
This subject continues the study of statistical inference beyond subject GAS2631. In particular, the subject develops inferential techniques for the general linear model and some extensions. Non-parametric inference and inference for finite population models are also covered. Topics include the general linear model, the method of least squares, estimability, the Gauss-Markov Theorem; hypothesis-testing including the likelihood ratio test for the case of normal disturbances, analysis of variance for experimental design models, the analysis of covariance, introduction to components of variance models, and logistic regression models; non-parametric methods including theory and application of simple tests based on ranks and runs; the goodness-of-fit problem; Kolmogorov-Smirnov statistics; sample survey theory including theory of simple and stratified random sampling, brief consideration of other sampling methods.
Assessment
Assignments: 50% * Examination: 50%
Prescribed texts
Nil. Students will be expected to use a range of library references.