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The University of Southampton

MATH6011 Forecasting

Module Overview

The module will introduce students to time series models and associated forecasting methods.

Aims and Objectives

Module Aims

• introduce the student to time series models and associated forecasting methods; • show how such models and methods can be implemented on a spreadsheet to analyse time series data; • give an appreciation of the different fields of application of time series analysis and forecasting; • convey the value of such quantitatively based methods for solving realistic practical problems..

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Formulate time series models and construct Excel spreadsheet-based versions
  • Use spreadsheet techniques to fit and analyse such models to data
  • Appreciate both the capabilities and the limitations of such computer based techniques
  • Produce well-structure assignment reports describing problem formulation and solution


Time Series Models: Decomposition, Analysis and Removal of Trends and Seasonality Exponential Smoothing Methods: Single Exponential, Holt and Holt-Winters Methods Simple and Multiple Regression Techniques Box-Jenkins Methods for ARIMA models

Learning and Teaching

Teaching and learning methods

Lectures and computer workshops.

Independent Study58
Total study time74

Resources & Reading list

Gilchrist, W.G. (1976). Statistical Forecasting. 

Rob J Hyndman and George Athanasopoulos (2012). Forecasting: principles and practice. 

Wetherill, GB. (1981). Intermediate Statistical Methods. 

Draper, N.R. and Smith, H. (1981). Applied Regression Abalysis. 

Anderson, R.A., Sweeney, D.J. and Williams, T.A. (1994). An Introduction to Management Science. 

Makridakis, S., Wheelwright, S.C. and Hyndman, R.J. (1998). Forecasting: Methods and Applications. 

Janert, P.K. (2011). Data Analysis with Open Source Tools. 



MethodPercentage contribution
Coursework 100%


MethodPercentage contribution
Coursework 100%


MethodPercentage contribution
Coursework 100%

Repeat Information

Repeat type: Internal & External

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