Statistical Methods (MPhil, MSc)

Course Provider: Professor David Kirk


The lectures aim to develop the foundations of statistical thinking and to introduce the most important statistical models used in social science research. The practical classes aim to give students the skills to undertake quantitative data analysis using Stata. 

This course is taught through an integrated series of lectures, given by Prof James Tilley, and hands-on classes, led by Prof David Kirk. The course is vertically structured: for the most part, later lectures assume knowledge of the foundational material covered earlier in the course. Topics covered include ideas of sampling and probability models, basic methods for inference about a population from a sample, and the use and interpretation of some common types of statistical models, including linear regression and logistic regression.

On successfully completing this course, students should:

  • understand the basic principles of statistical thinking;
  • be familiar with the most commonly used statistical models;
  • be able to implement standard statistical procedures (multivariate analysis as well as descriptive statistics) using Stata. 

Eight lectures plus eight hands-on classes in Michaelmas Term.

Students will be given three take-home assignments, which will involve analysing data and writing up the results in a formal manner. The first two assignments will be formative: group-work will be allowed, and marks will be given during Michaelmas Term. The final take-home assignment will be summative; students must work on this paper on their own, and the mark will form half of the final grade. The other half will be made up by a two hour in-class test.

• Agresti, A. and B. Finlay (1997/2009/2017) Statistical Methods for the Social Sciences, Pearson (3rd, 4th, or 5th edition; any will do).
• Hamilton, L.C. (2013) Statistics with Stata, Version 12, 8th Edition. Cengage