5.2. Learning Objectives#
5.2.1. Conceptual#
After this week, you should be able to:
Understand the principles underpinning logistic regression, including the logit transformation.
Recognise and interpret coefficients as log odds and odds ratios.
Be able to convert the output of logistic regression into predicted probabilities.
Understand the fit statistics for logistic regression.
These points will be covered in the lecture.
5.2.2. Python Skills#
We will be working with statsmodels
in Python again. This week, you will learn to:
Fit logistic regression models in Python.
Request model output in odds ratios.
Convert the model output into predicted probabilities.
Interpret basic model fit statistics.
Understand, and work with, the ‘effective sample’ in statistical models.