Authorised by Academic Registrar, April 1996
Objectives For students to continue the development of statistical methods introduced in quantitative methods 1; achieve basic understanding and appreciation of linear programming and its use in business decision making process; acquire skills and ability to formulate business decision problem as linear programming models; develop understanding and ability to interpret sensitivity analysis results; acquire skills for solving linear programming models using optimisation software; acquire knowledge and an understanding of elementary deterministic inventory management models; develop skills to perform hypothesis testing and ability to interpret the results of such tests; apply chi-square, analysis of variance and non-paramentric methods in hypothesis testing; enhance knowledge and skills in single and multiple linear regression calculations and interpretation of results; develop basic understanding of elementary methods of time series and forecasting.
Synopsis To develop the ability to perform quantitative analysis of a range of business problems, and draw inferences. The subject covers the following topics: (i) linear programming (the graphical solution procedure, introduction to the simplex method, dual simplex method, LP applications and use of computer packages); deterministic inventory models and business applications; time series (components, trend analysis, smoothing by moving averages, exponential smoothing); introduction to forecasting; (ii) statistics (point and interval estimation); hypothesis testing involving two independent and matched samples; non-parametric tests based on ranks; chi-squared test for independence; simple treatment of analysis of variance; review of simple linear regression, correlation analysis, multiple linear regression, curvilinear regression and exponential regression, using available computer packages.
Assessment Assignments: 40% + Examination: 60%