Not offered in 1999
6 points - Second semester - Distance
Objectives On completion of this subject, students will be able to describe the forecasting process through data analysis and model building, identify and apply both quantitative and qualitative forecasting techniques to practical problems to achieve efficiency in the utilisation of resources.
Synopsis Characteristics and essentials of forecasting, introduction to time-series data analysis, forecasting techniques including regression, moving averages, exponential smoothing, decomposition, subjective assessment methods, and Box-Jenkins ARIMA models. Use of spreadsheets and computer packages to prepare forecasts and compare different techniques.
Assessment Two assignments: 60% - Examination (3 hours): 40%
Prescribed texts
Makridakis S and others Forecasting: Methods and applications 3rd edn, Wiley, 1998
Recommended texts
Bowerman B L and O'Connell R T Time series forecasting:
Unified concepts and computer implementation 2nd edn, Duxbury, 1987
Newbold P and Bos T Introductory business forecasting South-Western,
1990