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MSc Economics / Course details

Year of entry: 2023

Course unit details:
Introduction to Quantitative Methods in Economics

Course unit fact file
Unit code ECON60901
Credit rating 0
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 1
Offered by Economics
Available as a free choice unit? Yes


The principal aim of this course is to refresh foundations of both Statistics and Math that will be used later on in the year from other modules

Learning outcomes

The principal aim of this course is to refresh foundations of both Statistics and Math that will be used later on in the year from other modules


For the Math Week, lectures will be structured as follows:

Lecture 1: Set, Numbers and Function

Lecture 2: Univariate Calculus and Optimization

  • Derivative and Differentials
  • Unconstrained Optimization;
  • Constrained Maximization.

Lecture 3: Linear Algebra

  • Matrix algebra
  • Quadratic Forms.

Lectures 4: Multivariate Calculus and Optimization

  • Partial Derivatives
  • Functions with Economics Applications
  • Unconstrained Maximization
  • Constrained Maximization

Lectures 5: Integration

  • Indefinite Integrals
  • Definite Integrals


Lecture 1: Probability & Moments

Lecture 2: Joint Distribution Theory

Lecture 3: Random Sampling & Estimation

Lecture 4: Confidence Intervals & Testing

Lecture 5: OLS and Intro to ECON60901 (Compulsory only for MSc Students)


Teaching and learning methods


Assessment methods

Online exam.

Recommended reading


Here is an outline of what we expect students to know, as a minimum, before they start the pre-session course and the areas that the course covers. This list will help you to plan any necessary revision.

You will find it useful to refer to Ian Jacques, Mathematics for Economics and Business, 5th Edn. (2006), Prentice-Hall. ISBN: 10 0-273-70195-9

  1. Notation and symbols including Greek letters
  2. Indices, powers or exponents (See Jacques pp.141-152)
  3. Linear equations (See Jacques, Chapter 1)
  4. Non-linear equations and functions (See Jacques, Chapter 2)
  5. Compound interest and series (See Jacques, Chapter 3)
  6. Differentiation (See Jacques, Chapter 4)
  7. Partial differentiation (See Jacques, Chapter 5)
  8. Integration (See Jacques, Chapter 6)
  9. Basic matrices (See Jacques, Chapter 7)

For a concise summary of the required knowledge of statistics see also our dedicated Econometric Computing Learning Resource (ECLR).


Teaching staff

Staff member Role
Robert O'Neill Unit coordinator
Alessia Isopi Unit coordinator

Additional notes

Lecturers: Alessia Isopi and Rob O'Neill.


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