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Time Series - MAT00045H

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  • Department: Mathematics
  • Module co-ordinator: Prof. Wenyang Zhang
  • Credit value: 10 credits
  • Credit level: H
  • Academic year of delivery: 2017-18

Module will run

Occurrence Teaching cycle
A Spring Term 2017-18

Module aims

This module is to introduce a variety of statistical models for time series and cover the main methods for analysing these models.

Module learning outcomes

At the end of the module you should be able to...

Compute and interpret a correlogram and a sample spectrum

derive the properties of ARIMA models

choose an appropriate ARIMA model for a given set of data and fit the model using an appropriate package

compute forecasts for a variety of linear models.


Task Length % of module mark
University - closed examination
Time Series
2 hours 100

Special assessment rules



Task Length % of module mark
University - closed examination
Time Series
2 hours 100

Module feedback

Information currently unavailable

Indicative reading

Chatfield, C. (2004). The analysis of time series. 6th Edition. Chapman & Hall
Brockwell P.J. and Davis R.A. (1991). Time series: theory and methods. Springer-Verlag
Harvey, A. (1989). Forecasting, structural time series models and the Kalman filter. Cambridge University Press.

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.