Authorised by Academic Registrar, April 1996
Objectives On completion of this subject students should recognise the need for using an experiment or a sample survey for collecting data, and the nature of data arising from these situations; have developed an understanding of some of the important parametric and nonparametric methods of statistical data analysis; be able to choose and apply a statistical technique (from those covered in the subject) suitable for analysing a given set of data; have acquired skills to develop a model relating a response variable to a number of given independent variables; be able to use a statistical package for applying statistical techniques covered in the subject.
Synopsis This subject is designed to develop an understanding of some of the most widely used methods of statistical data analysis, from the viewpoint of the user, with an emphasis on planned experiments. Students will become familiar with at least one standard statistical package. Topics covered include parametric and non-parametric procedures to compare two independent and matched samples; review of simple linear regression; multiple linear regression - analysis of residuals, choice of explanatory variables; non-linear relationships; basic principles of experimental design; one-way and two-way analysis of variance models; multiple comparison techniques; Kruskal-Wallis test; basic sampling techniques including simple random sampling and stratified random sampling; usage of some available statistical packages including MINITAB, data preparation, interpretation of output.
Assessment Assignments: 40% + Examination: 60%