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. Proud |

Open unit status | Not open |

Pre-requisites |
A-level Mathematics (or equivalent) |

Co-requisites |
None |

School/department | School of Economics |

Faculty | Faculty of Social Sciences and Law |

This unit aims to equip students with the basic mathematical and statistical tools most widely used in Economics, Finance, Accounting and Management.

On the mathematical side, the unit covers basic multivariate calculus, mainly partial differentiation, constrained and unconstrained optimisation, and simple integration.

On the statistical side, the unit covers fundamental ideas of mathematical statistics, including concepts such a random variable, a probability distribution function, an expected value, a variance and a covariance.

Students will be able to:

1. Demonstrate competence in differentiating multivariate functions with respect to a variable.

2. Solve unconstrained optimisation problems.

3. Solve optimisation problems with equality constraints using the Lagrangian method.

4. Understand the concept of integral and be able to compute a variety of simple integrals

5. Identify an economic, financial or management problem that is expressed in mathematical form.

6. Demonstrate an ability to express real world problems in a mathematical form.

7. Explain important statistical concepts such as sample space, probability of an event, conditional probability, random variable, marginal distributions, expected value and sampling distribution.

8. Calculate statistics such as a mean or a covariance and be able to interpret them.

9. Understand the theory of estimation and hypothesis testing.

35 Lectures/Exercise Lectures

10 classes

Summative assessment:

2.5-hour examination in January worth 100%. This tests all the learning outcomes.

Formative Assessment:

Students will submit **two** long assignments, which will consist of 50% mathematics and 50% statistics, which will be marked and returned.

In addition, students will be expected to complete regular problem sets in advance of classes.

Sydsaester, K. and Hammond, P., Essential Mathematics for Economic Analysis, Prenctice Hall.

Stock J. and Watson M. (2007) Introduction to Econometrics 3rd edition Pearson Education, New York

Gujarati D. and D. Porter (2010) Essentials of Econometrics (4th Edition) McGraw Hill Irwin

Cranshaw J. and J. Chambers (2001) A concise course in A level Statistics fourth edition Nelson Thornes

Mendenhall, Schaeffer and Wackerly (1990) Mathematical Statistics with applications (4th Edition) Boston: Duxbery Press