Generalized Linear Model

A Generalized Linear Model (GLM) is a flexible statistical method used to understand the relationship between a set of input variables (predictors) and an outcome that may not follow a normal distribution. Unlike simple linear models, GLMs can handle various types of data, such as counts, categories, or proportions. They work by connecting the predictors to the outcome through a special function called a link function, allowing for accurate modeling of diverse data types and improving prediction and understanding of complex relationships in fields like medicine, economics, and social sciences.