What you'll learn

Create contingency tables
Calculate odds ratio
Understand what is logistic regression
Identify when logistic regression is used
Understand the output produced by logistic regression
Include categorical variables
Test for linearity
Predict probabilities
Test model fit
Apply logistic regression using Stata
Visualise the best-fit model

Requirements

Have a basic understanding of linear regression

Description

Included in this course is an e-book and a set of slides. The course is divided into two parts. In the first part, students are introduced to the theory behind logistic regression. The theory is explained in an intuitive way. The math is kept to a minimum. The course starts with an introduction to contingency tables, in which students learn how to calculate and interpret the odds and the odds ratios. From there, the course moves on to the topic of logistic regression, where students will learn when and how to use this regression technique. Topics such as model building, prediction, and assessment of model fit are covered. In addition, the course also covers diagnostics by covering the topics of residuals and influential observations.

In the second part of the course, students learn how to apply what they learned using Stata. In this part, students will walk through a large project in order to understand the type of questions that are raised throughout the process, and which commands to use in order to address these questions.

Who this course is for:

Beginner non-mathematical students who want to use logistic regression