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The University of Southampton

MANG2065 Business Forecasting

Module Overview

This course provides part of the essential knowledge and skills required for conducting the Final Project module in the final year. Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. This module gives you a thorough understanding of various statistical methods for forecasting, in particular time-series methods that have wide applications in business. Risk and uncertainty are central to forecasting and prediction; it is generally considered good practice to indicate the degree of uncertainty attaching to forecasts, and sometimes it is necessary to provide distributional rather than point forecasts. As such, an introduction to methods for distributional forecasting will also be provided. As forecasting often requires huge amount of data, both for training and testing the models, and the required formulae and equations are often complicated, it is essential to implement forecasting methods using a proper statistical package. As such training will be provided on using R and SAS package for implementing forecasting methods.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • different fields of application of time series analysis and forecasting;
  • the capabilities as well as limitations of quantitative-based forecasting methods;
  • the importance of incorporating uncertainty in forecasting.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • formulate time series models including exponential smoothing methods, ARIMA methods, and innovations state space models;
  • use advanced statistical tools to fit and analyse such models to data;
  • choose the most appropriate forecasting method using various types of information criterion.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • self-manage the development of learning and study skills;
  • plan and control effectively for successful completion of a personal workload;
  • communicate effectively, in both oral and written form, using and justifying argument within reports and presentations.


The topics covered in this module will include: • Introduction to Forecasting: quantitative and qualitative methods; • Time series models: decomposition, analysis and removal of trend, seasonality, and cycle; • Exponential Smoothing Methods: Single Exponential, Holt and Holt-Winters Methods; • Box-Jenkins Methods for ARIMA models; • Simple and Multiple Regression Techniques; • Introduction to Innovations State Space models.

Learning and Teaching

Teaching and learning methods

Teaching methods include: • Lectures • Interactive case studies • Problem-solving activities • Computer labs • Directed reading • Private/guided study. Learning activities include: • Introductory lectures • An assignment (individual written coursework) • Case study/problem solving activities • In class debate and discussion • Private study • Use of video and online materials

Completion of assessment task70
Supervised time in studio/workshop12
Preparation for scheduled sessions20
Follow-up work24
Total study time150

Resources & Reading list

SAS Base Software. R and SAS Software. This module will require the weekly use of a computer lab equipped with the latest version of SAS Base Software and R programming Language. R is open source programming software and you can download in your computer freely. You can install the SAS software from iSolutions.

Hyndman, R.J. and Athanasopoulos, G (2013). Forecasting: Principles and Practice. 



Student presentation


MethodPercentage contribution
Report  (3000 words) 100%


MethodPercentage contribution
Report  (3000 words) 100%


MethodPercentage contribution
Report  (3000 words) 100%

Repeat Information

Repeat type: Internal & External

Linked modules

Pre-requisite: MANG2062


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the mandatory/additional reading text as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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