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Unit information: Mathematical and Statistical Methods in 2020/21

Unit name Mathematical and Statistical Methods
Unit code EFIM10008
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Somekh
Open unit status Not open

A-level Mathematics (or equivalent)



School/department School of Economics
Faculty Faculty of Social Sciences and Law


The study of economics requires students to use mathematical techniques to model agents’ behaviour, and to use statistical tools to, for example, analyse the impact of economic policy. This unit provides the basic mathematical tools that students will require to study economics units, and the statistical foundations required to analyse economic data. Topics covered will include an introduction to:

  • Univariate and multivariate calculus
  • Partial differentiation
  • Optimisation
  • Constrained optimisation
  • Integration
  • Probability

Basic statistics including the fundamentals of hypothesis testing

Intended learning outcomes

Students will be able:

  1. To manipulate mathematical formulae to obtain solutions to well-defined problems;
  2. To understand how mathematical notation can be used to make economic and statistical problems more precise
  3. To interpret economic or statistical problems and analyse these using appropriate mathematical techniques and to evaluate solutions.

Teaching details

Teaching will be delivered through a combination of synchronous and asynchronous sessions such as online teaching for large and small group, face-to-face small group classes (where possible) and interactive learning activities

Assessment Details

Mathematics problem-based assignment (25%) Probability/Statistics-based assignment (25%) Examination (50%) Each assessments assess all learning outcomes

Reading and References

There is no fixed textbook for this unit, but the following texts may be useful:


  • Renshaw, G., (2012) Maths for Economics, OUP
  • Sydsaeter, K. and Hammond, P., Essential Mathematics for Economic Analysis, Prentice Hall.


  • Crawshaw, D.J., and Chambers, J.S. (2013) A concise course in Advanced Level Statistics with worked examples