Poisson Regression

Poisson regression is a statistical method used to model count data—that is, data showing the number of times an event occurs, such as accidents or customer visits. It relates these counts to one or more factors or predictors, like weather or time of day, to understand how they influence event frequency. The model assumes that the counts follow a Poisson distribution, meaning the events happen randomly but with a certain average rate that can change based on the predictors. This helps predict future counts and assess how different factors impact the likelihood of the event happening.