MY552      Half Unit
Applied Regression Analysis

This information is for the 2019/20 session.

Teacher responsible

Dr Indraneel Sircar COL.7.04 (LT) and Dr Daniele Fanelli

Daniele Fanelli (MT)

Indraneel Sircar (LT)


This course is available on the MPhil/PhD in Cities Programme, MPhil/PhD in Data, Networks and Society, MPhil/PhD in European Studies, MPhil/PhD in Health Policy and Health Economics, MPhil/PhD in Media and Communications, MPhil/PhD in Psychological and Behavioural Science, MPhil/PhD in Social Policy, MPhil/PhD in Social Research Methods, MPhil/PhD in Sociology, MRes/PhD in Management (Marketing), MRes/PhD in Management (Organisational Behaviour) and MRes/PhD in Political Science. This course is available as an outside option to students on other programmes where regulations permit.

Research students where programme regulations allow.


Students are required to have completed MY451/MY551 Introduction to Quantitative Analysis or an equivalent level statistics course.

Course content

The course is designed for students with a good working knowledge of elementary descriptive statistics; sampling distributions; one and two sample tests for means and proportions; correlation and the linear regression model with one or more predictor variables. The course is concerned with deepening the understanding of the generalized linear model and its application to social science data. The main topics covered are linear regression modelling and binary, multinomial and ordinal logistic regression. 


20 hours of lectures and 10 hours of computer workshops in the MT. 20 hours of lectures and 10 hours of computer workshops in the LT.

This course is given twice per session, starting in the first week of each of the MT and LT. Students must either register for MY552M which is taught in Michaelmas Term, or MY552L which is taught in Lent Term.

There will be no lectures or computer classes in Week 6 of term.

Formative coursework

Exercises from the weekly computer classes can be submitted for feedback.

Indicative reading

A Agresti & B Finlay, Statistical Methods for the Social Sciences. A course pack will be available for download online. Additional reading will be recommended.


Exam (100%, duration: 2 hours) in the summer exam period.

Two hour unseen examination in ST. Students are permitted to bring a limited quantity of written notes into the examination.

Key facts

Department: Methodology

Total students 2018/19: Unavailable

Average class size 2018/19: Unavailable

Value: Half Unit

Guidelines for interpreting course guide information