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The University of Southampton

MANG1028 Statistical Methods for Finance

Module Overview

Statistical Methods for Finance is a critical module for you to learn basics for future modules on Econometrics, as well as their final year dissertation. This module covers important topics such as probability, discrete and random variables, Probability distributions, normal distribution, hypothesis testing, graphical analysis, correlation and simple regression. Lectures are followed by in-depth practical examples using tools that show the real world implications.

Aims and Objectives

Module Aims

to introduce you to basic probability theory, so that decision making under uncertainty can be analysed as well as develop an understanding of estimation and inference as a foundation for applied finance. This module is an introduction to statistics and data manipulation and the module deals with the fundamental issues of statistics building from basic probability theory, through sampling, distributions, hypothesis testing and interpretation. A wide range of examples are considered.

Learning Outcomes

Knowledge and Understanding

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

  • basic probability theory, through sampling, distributions, hypothesis testing and interpretation.
  • how to analyse financial data
  • the importance and use of a normal distribution
  • the key differences between correlation and causation
Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • to conduct probability tests under various situations and value assets
  • to perform hypothesis testing using a normal distribution
Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • Demonstrate competence generally in numerical analysis and problem solving
  • Apply numeracy and quantitative analysis skills


Probability Discrete and random variables Probability distributions The normal distribution Hypothesis testing Graphical analysis Correlation Simple regression

Learning and Teaching

Teaching and learning methods

Weekly lectures will provide an overview of the main issues arising in the module. Weekly classes will supplement the lectures which will support student learning by providing opportunities for students to attempt, and gain feedback on, numerical and problem-solving exercises. Students will also have the opportunity for both directed and non-directed independent reading

Follow-up work26
Preparation for scheduled sessions10
Wider reading or practice30
Total study time150

Resources & Reading list

Newbold, Paul Carlson, William L (2013). Statistics for business and economics. 

Koop, Gary. Analysis of economic data. 



In-class activities


MethodPercentage contribution
Examination  (1 hours) 30%
Examination  (2 hours) 70%


MethodPercentage contribution
Examination  (2 hours) 100%


MethodPercentage contribution
Examination  (2 hours) 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:

Printing and Photocopying Costs

There will be additional costs for printing.


Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase the core/recommended 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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