Leader: Associate Professor Philip Rayment
Gippsland First semester 2006 (OCL)
Synopsis: This unit 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.
Objectives: On completion of this unit, students should be able to recognise the requirements for design of an effective experiment and the nature of data arising from these situations; demonstrate an understanding of some of the important parametric methods of statistical data analysis, including analysis of variance, multiple linear regression and logistic regression; select and apply a statistical technique (from those covered in the unit) suitable for analysing a given set of data; formulate a model relating a response variable to a number of given independent variables; use a statistical package for applying statistical techniques covered in the unit.
Assessment: Assignments (two): 30% + Examination (3 hours): 70%
Contact Hours: Three 1-hour lectures and one 1-hour workshop per week
Prohibitions: MAT2236, GAS3631, MAT3211, MAT3221, MAS3111, MAS3121, MTH2246