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Department of Economics

Statistical Research Techniques

Course Code:
Unit value:
Taught in:
Term 2

(This module is only available to students taking the MSc Political Economy of Development)

The aims of Research Methods I are threefold: 

  1. to introduce students to basic inference and a range of statistical test; 
  2. to encourage the clear and coherent expression of statistical results; 
  3. and to promote the critical reading of statistics within the economics literature.

The course is designed for students with little previous knowledge of statistics. The topics covered will include sampling methods, the comparison of means, the analysis of contingency tables, correlation and basic regression. The software package Stata 9.0 will be used throughout the course. Open access computers at SOAS are available for students to complete the course work.


The preliminary Mathematics and Statistics course is a pre- requisite to the course. Those students performing well on the exam may be given the opportunity to take Quantitative Methods I as an alternative to Statistical Research Techniques, but would then be required to take Quantitative Methods II as an option.

Objectives and learning outcomes of the course

The learning outcomes are as follows:

  • The ability to generate and interpret descriptive statistics for both categorical and continuous data
  • An understanding of the underlying principles and an ability to use confidence intervals and hypothesis tests
  • The ability to generate and interpret measures of association for categorical data using contingency tables, conditional distributions, tests of independence, residuals and odds ratios
  • An understanding of the mechanics of coding a questionnaire
  • An understanding of the main principles of survey design, including sources of sampling and non-sampling error
  • The ability to compare means, including one-sample t-tests, paired sample t-tests, independent sample t-tests, and one-way ANOVA
  • A basic understanding of estimation, inference and validation of the Classical Linear Regression model.
This will include the ability
  • to interpret and test the estimated coefficients from simple bivariate regressions and multiple regressions
  • to test the goodness and fit of the model
  • to validate the main assumptions of the estimation procedures
  • to use the log-linear functional form
  • to use dummy variables to include categorical variables on the right-hand side of the equation, i.e. as independent variables

Method of assessment

Assessment weighting: Exam 100%.

Suggested reading

  • Agresti, Alan and Finlay, Barbara (1997) Statistical Methods for the Social Sciences, 3rd Ed. Prentice-Hall Int. ISBN0-13-622515-2.
  • Gujarati, Damodar N. and D. C. Porter (2009) Basic Econometrics, 5th Ed. McGraw-Hill. ISBN 978-007-127625-2.
  • Howell, David C. (2002) Statistical Methods for Psychology, 5th Ed. Duxbury/Thomson Learning. ISBN 0-534-37770-X.
  • Mukherjee, C, White, H., Wuyts, M (1998) Econometrics and Data Analysis for Developing Countries, Routledge. ISBN: 0-415-09400-3
  • Thomas, R.L. (2005) Using Statistics in Economics, McGraw-Hill. SOAS Library: A519.5/936748
  • Wooldridge, J. M. (2003) Introductory Econometrics: A Modern Approach, Mason, Thomson. ISBN 0-324-11364-1.