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The University of Southampton

MANG6003 Quantitative Methods

Module Overview

MANG6003 aims to develop statistical reasoning. Via a series of examples and activities, students are introduced to the idea of probability modelling and how it can be applied to aid decision making in uncertain situations, which are frequently encountered in organisations. On successful completion of this module, students should be able to collect relevant data and summarise the main features of an uncertain situation, to identify standard problems and analyse them with the correct statistical tools, to process and analyse data in a statistical computer package, to understand the risks involved in a decision which involves uncertainty, and quantify such risks. Students should also develop problem solving skills, modelling skills, become familiar with a standard statistical computer package (SPSS), and be able to interpret and critically evaluate statistical results.

Aims and Objectives

Learning Outcomes

Knowledge and Understanding

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

  • what is statistical reasoning and how it can be applied to aid decision making;
  • how historical data can be used to find patterns and trends; and report on past performance;
  • what probability distributions are and how they are used to aid decision making;
  • what is hypothesis testing and how hypothesis testing can be used within the statistical modelling process.
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • identify standard problems involving uncertainty and analyse them with the correct statistical techniques;
  • understand the risks involved in a decision which involves uncertainty, and quantify such risks;
  • calculate probabilities from theoretical and empirical distributions and use the results to make inferences about decision problem situations;
  • evaluate the existence of relationships among variables.
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • collect relevant data and summarise the main features of an uncertain situation;
  • process, analyse and display data in a statistical computer package (SPSS);
  • develop technical, analytical, critical thinking and presentational skills;
  • work effectively in a team.


• Statistical reasoning, repeated experiments, random variables. • Measures of central tendency and spread. Statistical moments. • Symmetry and pointedness. • Confidence limits. • Standardised data. • Extreme observations. • Continuous and discrete data. • Introduction to probability. • Addition and multiplication rules. • The method of maximum likelihood. • Probability distribution. • Cumulative probability distribution. • Simulation as a tool to solve statistical problems. • Pseudo-random numbers. • Some standard distributions: Binomial distribution, Poisson distribution, Normal distribution, Chi-square distribution. • Sampling of quality. • The characteristic function of a sampling plan. • The power of a statistical test. • Hypothesis testing. • Analysis of contingency tables. • Combination of random variables. • Central limit theorem. • Association and correlation. • Measures of association. • Linearity and non-linearity. • Spurious correlation. • Regression. • Least squares. • T-tests. • Serial correlation.

Learning and Teaching

Teaching and learning methods

Teaching involves student participation, games, and creative thinking. Students are expected to actively participate in the class. For instance, utilising generally accepted games of chance (such as coin tossing), students engage actively with statistical concepts. Furthermore, case studies are provided during the lectures which ask student to identify and analyse data sets in order to support the development of their problem solving skills and their ability to identify the most appropriate quantitative methods for addressing a given (often uncertain) situation. A full description of each lecture is distributed in advance. In addition to the case studies and activities numerous examples are provided in the lectures. All of these activities contribute to students’ understanding of the subject matter and shape their ability to apply these skills in their assessments. Teaching methods include: Lecturing and multimedia demonstration (video) Learning activities include: Case study, group discussion, game playing-tossing coin, problem solving exercises

Independent Study126
Total study time150

Resources & Reading list

Morris C (2003). Quantitative Approaches in Business Studies. 

Robertson, C (2002). Business Statistics: A Multimedia Guide to Concepts and Applications. 

Wisniewski, M (2006). Quantitative Methods for Decision Makers. 

Anderson, D.R., Sweeney, D.J., Williams, T.A., Freeman, J. and Shoesmith, E (2009). Statistics for Business and Economics. 

Lind, D.A., Marchal, W.G. and Wathen, S. (2007). Statistical Techniques in Business and Economics with Student CD. 



Peer Group Feedback


MethodPercentage contribution
Individual Coursework 80%
Multiple choice Test 20%


MethodPercentage contribution
Individual Coursework 100%


MethodPercentage contribution
Individual Coursework 100%

Repeat Information

Repeat type: Internal & External


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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