Module Directory

This module introduces students to the methods of quantitative economics, i.e. to how data are used in economics. Beginning from an elementary level (assuming no background in statistics), the course shows how economic data can be described and analysed.

The elements of probability and random variables are introduced in the context of economic applications. The probability theory enables an introduction to elementary statistical inference: parameter estimation, confidence intervals and hypothesis tests. With these foundations, students are then introduced to the linear regression model that forms a starting point for econometrics. Throughout the course the emphasis is on the practical application of economic analysis from an empirical perspective.

The aim of this module is:

• To enhance students' knowledge and conceptual understanding of the treatment of data in economics.

By the end of this module, students will be expected to:

1. Be aware of the main sources of economic data; know how to construct and interpret graphs of the data; know how to construct summary statistics.


2. Have acquired a knowledge of the statistical methods needed for the analysis of economic issues.


3. Have learned how to interpret the estimates of simple economic models and to conduct tests of hypotheses about the model's parameters.

Skills for your Professional Life (Transferable Skills)

The module provides the students with a wide set of tools which will prove to be particularly relevant during their working careers.

1. Their ability to read, understand and properly manipulate data will be strongly enhanced, from both a theoretical and empirical point of view.


2. Students are introduced to the knowledge of widely used statistical computational packages and plenty of examples from real datasets will reinforce student's control of the most important statistical techniques.

First year students with a background in mathematics may substitute EC114 for the more advanced modules MA114 and MA108 offered by the department of Mathematical Sciences with permission from the department.

The module will be delivered via:

• Two lectures per week.
• One class per week.
• Support class.

Feedback for this module will occur through class meetings where we will go over the answers to problem sets and where you will be able to ask questions about your own method of solution; answers that will be posted on the website for the module that will give you written guidance on the appropriate method to approach the problems, assignments, and tests; and office hours where any additional questions can be addressed. You should be sure that you use these methods to understand how to improve your own performance. For modules including a term paper, the term paper will be returned with individualised feedback that addresses what the marking criteria are and how you could improve your own work.