(SCI)
Associate Professor Philip Rayment
6 points + First semester in even numbered years + Three 1-hour lectures and one 1-hour workshop per week + Gippsland/Berwick/Distance + Prerequisites: MAT1060 or MTH1210 + Prohibitions: MAT2236, GAS3631, MAT3211, MAT3221, MAS3111, MAS3121
Synopsis: This subject is designed to develop an understanding of some of the most widely used methods of statistical data analysis, from the view point of the user, with an emphasis on planned experiments. Students will become familiar with at least one standard statistical package. Topics covered include: multiple linear regression - analysis of residuals, choice of explanatory variables; model selection and validation; nonlinear relationships; introduction to logistic regression; principles of experimental design; analysis of variance models; planned and multiple comparison techniques; quality management; use of statistical packages.
Assessment: Assignments (two): 30% + Examination (3 hours): 70%