Authorised by Academic Registrar, April 1996
6 points + Second semester + Distance
Objectives On completion of this subject, students should be able to describe the forecasting process through data analysis and model building; and identify and apply both quantitative and qualitative forecasting techniques to practical problems
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%