Authorised by Academic Registrar, April 1996
Objectives On the completion of this subject students will have a knowledge of some of the important theoretical and applied aspects of time series analysis and forecasting; understand the knowledge required not only for the methods and techniques, but also for applying the time series methods to practical problems in various areas of human activity; have practical experience by being exposed to problems based on real data; be able to use computing packages such as MINITAB and ITSM.
Synopsis Introduction to time series, smoothing techniques, stationary and non-stationary time series, seasonal and non-seasonal time series, ARIMA models, MINITAB and ITSM packages in time series.
Assessment Examinations (1.5 hours): 80% + Assignments: 20%