Introductory description

This module allows students to develop an understanding of fundamental and intermediate concepts of statistical analysis, such as regression analysis. Students will also develop the capacity to apply statistical techniques to real world problems/data sets using the statistical package STATA.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

The module will typically cover the following topics:
Review of random variables, associated distributions and moments; review of statistical estimation, estimator sampling distributions and population inference; causality and selection bias; experimental versus non-experimental data; simple linear regression (SLR) model, assumptions, interpretation and hypothesis testing; multiple linear regression (MLR) model, assumptions, interpretation and hypothesis testing; modelling non-linear relationships; dummy variables; interaction terms; the failure of MLR assumptions; tests and implications for hypothesis testing; problems of endogeneity; instrumental variables; short panel data methods; Stata.

Learning outcomes

By the end of the module, students should be able to:

• Subject Knowledge and Understanding:...demonstrate understanding of random variables, associated distributions and moments; statistical estimation, estimator sampling distributions and population inference; causality and selection bias; experimental versus non-experimental data; simple linear regression (SLR) model, assumptions, interpretation and hypothesis testing; multiple linear regression (MLR) model, assumptions, interpretation and hypothesis testing; modelling non-linear relationships; dummy variables; interaction terms; the failure of MLR assumptions; tests and implications for hypothesis testing; problems of endogeneity; instrumental variables; short panel data methods; Stata.
• Knowledge and understanding of:... (i) Economic Principles including analysis of economic decisions in microeconomics. (ii) An awareness of the empirical approach to economics and social science. (iii) Reviewing and extending fundamental statistical concepts, including causal analysis and (iv) Regression analysis, its extensions and applications.

Indicative reading list

Reading lists can be found in Talis

Specific reading list for the module

Research element

Students will be required to undertake a 2000 word data research project.

Subject specific skills

Applied Economics
Economic information
Economic principles
Research and debate
Abstraction
Analysis of incentives
Analytical reasoning
Analytical thinking and communication
Creative thinking
Critical thinking
Policy evaluation
Problem solving
Strategic thinking

Transferable skills

Data-based skills
IT skills
Numeracy and quantitative skills
Research skills
Information technology
Math, Statistical, data-based research skills
Oral communication
Team work skills
Written communication
Coding Skills (Stata)