What are logit and probit models?

Logit and probit models are statistical techniques used for modeling binary outcome variables, where the response can take one of two possible values (e.g., success/failure). The logit model uses a logistic function to model the probability of an event occurring, while the probit model employs the cumulative distribution function of the standard normal distribution. Both models estimate the relationship between independent variables and the probability of the dependent variable being one of the outcomes, but they differ in their underlying assumptions and mathematical formulations. These models are commonly used in fields such as economics, sociology, and biomedical research for classification and prediction tasks.