Handbook 1996 : Faculty of Science (Volume 4 page 238)
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619-360 Time Series and Forecasting

Note: Special requirement: An electronic calculator of an approved type (refer to Department of Statistics Office).

Credit points: 15.0

Coordinator: Dr GK Grunwald

Prerequisite: Statistics 619-330

Contact: 39 lectures (three a week)

Timetable: Second semester

Objectives:

Students completing this course should

Comprehend:

• the concept of a time series;
• the usefulness of time series analysis;
• the basic principles of time series analysis in the time domain and in the frequency domain;
• simple models for time series;

Have developed the skills:

• to use standard forecasting techniques;
• to carry out simple time series analyses in the time domain and in the frequency domain;
• to use the computer as an aid to efficient analysis of time series;

Appreciate:

• the patterns inherent in real-world time series;
• the importance of the underlying mathematical theory of time series;
• the application of computer software in the analysis of time series.

Content:

Patterns in time series. Simple methods for exploratory data analysis: smoothing techniques. Smoothing and decomposition. Trends and seasonal variation. Simple forecasting methods: mean, last value. Accuracy of forecasts. Exponential methods. Models for time series: stationarity, autocorrelation; ARMA processes; ARIMA processes. Estimation and model fitting. Spectral analysis. Smoothing by Fourier series. Linear filtering.

Assessment:

Up to 3 hours end-of semester written examination; up to 50 pages of assignments may be assessed.

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Handbook 1996 : Faculty of Science (Volume 4 page 238)

Status:          Official 1996
Date created:    Oct  9 1995
Last modified:   Oct  9 1995
Authorised by:   Academic Registrar
Email enquiries: Course_Information@registrar.unimelb.edu.au

Copyright © University of Melbourne 1995,1996.