Logistic Regression

Date: 3 May 2023
Time: 9.30am-4.30pm
Instructor: Tatjana Kecojevic
Level: Introductory 
Fee: £60

Please note that this course is open to University of Manchester staff and students only. 

To book on to this course, please email cmi@manchester.ac.uk for further details.


This course examines the fitting of models to predict a binary response variable from a mixture of binary and interval explanatory variables, using the statistical software called R.

The approach is illustrated using examples from a social science perspective, including cases where logistic regression models are used as a means of analysing tabular data where one of the dimensions of the table is a two-category outcome variable.

You will also learn how to fit a logistic regression model, and how to interpret the results.


At the end of the course participants should be able to:

  • Understand the concepts of odds and odds ratios.
  • Generate odds for given contingency tables. 
  • Understand the basic theory behind binary logistic regression. 
  • Run and interpret a logistic regression model. 
  • Interpret Log Likelihoods to evaluate models.
  • Choose between different models.


Some knowledge of the R programming language and basic understanding of regression would be helpful. 

About the instructor