## Skill Introduction

In this skill we will use the logit function to extend regular regression to situations in which the outcome has only two values. After illustrating that the logit function is the log of the odds ratio, and developing some intuition surrounding that idea, we will demonstrate how logistic regression can be run using R code. We talk about how to interpret the outcome, including how to convert the logit value to a probability that is easier to understand.

## Learning Outcomes

Upon successful completion, you will be able to:

• Develop an understanding of probability, odds, and logit

• Experiment with creating logistic regression models in R

• Interpret the diagnostic results of logistic regression models

• Use a logit model to create predictions about the probability that an event will occur

## Course curriculum

• 1

### Orientation

• Interview with Monica Penagos - Choice Models in Practice

• Introduction to the Skill

• Glossary

• 2

### Content and Activities

• Binary Outcome Model - Logit Model

• Knowledge Check 1

• Logit Model - Example 1

• Knowledge Check 2

• Logit Model - Example 2

• Knowledge Check 3

• 3

### Application Exercise

• Instructions

• Exercise Files

• Debriefing

• 4

### Summary

• Conclusion

• Final Quiz

• Survey Instructions

• Feedback Survey

• Survey Verification

• Next Steps