UCL School of Slavonic and East European Studies (SSEES)


SEES0083 Quantitative Methods

UCL Credit Value: 15

ECTS Value: 7.5

Term 1

Taught By: Randolph Bruno and Luca J. Uberti

Weekly Contact Hours: 3.0
Prerequisites: Introductory Level Economics
This module is compulsory for students on the following programmes:
MA Comparative Business Economics
MA Comparative Economics and Policy
MRes in the Politics and Economics of Eastern Europe
MRes in East European Studies (Year 2 Social Sciences track)
IMESS (Economcs & Business track)
This module is a prerequisite for SEESGS46 Advanced Quantitative Methods

Summative Assessment

2 hour examinations (50%), 3,000 word coursework (50%)

Formative Assessment

Tutorials are run weekly at a computer lab, where students will be expected to complete exercises in the use of STATA, a statistics software package. The tutor will run part of the tutorial as a small class, giving the students some basic motivation and a starting point. The students will then complete the remainder of the exercises on their own or in small groups with the tutor providing on-the-spot assistance and feeding any relevant advice back to the class as a whole.

Module Outline

This graduate module assumes no prior knowledge of statistics or knowledge of mathematics beyond GCSE (or equivalent). It provides a basic introduction to statistics essential for multi-disciplinary study. The emphasis is on elements of statistical thinking and insight is drawn from simple data and concepts rather than complex derivations and formulae. The module presents quantitative methods as an essential intellectual method appropriate for study alongside other approaches to social sciences. The module is oriented towards making practical use of simple statistical methods and is focused particularly on interpretation of the results. The second part of the course introduces students to regression analysis and so prepares them for more advanced courses in quantitative methods and econometrics (SEESGS46). By the end of the course all students will be able to conduct and interpret simple empirical statistical analysis with the use of real world data. The course uses the STATA software package. 

Key Readings

  • Newbold, P., Carlson, W. Thorne, B. (2012) Statistics for Business and Economics, 8/E, Pearson, chapters 1 to 13 and 15 (for lectures)
  • Levin, J. and Fox, J. A. (2010), Elementary Statistics in Social Research: The Essentials, 3rd Edition. Boston, MA: Pearson (selected parts only, for lectures)
  • Kohler, U. and Kreuter, F., (2012), Data Analysis Using STATA, 3rd Edition, STATA press (for tutorials)

Please note: This outline is accurate at the time of publication. Minor amendments may be made prior to the start of the academic year.