Title: Tutorial Exercise: Logistic regression
Course: UGQuants (SSPS) > Section: Logistic Regression

Tutorial Exercise

Having familiarised yourself with multiple linear regression model building last week, it is your task this week to build a binary logistic regression model. You could do this, for example, by trying to predict whether someone is likely to use the internet regularly or not (the binary internet use variable is provided in the ESS5 practice dataset, but if you prefer the bigger sample and wider variety of variables of the full ESS5 dataset, you can create a binary variable there yourself through recoding). Use both continuous and categorical explanatory variables in your model.

Make sure you understand:

- how to interpret B and Exp(B),
- how to enter categorical variables into the model,
- why the model never shows all categories of an explanatory variable (reference category),
- how to assess the model fit.