Learning Objectives

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.

Contents