Poisson Regression Model
  • is a type of count regression model
  • Count data frequently follow the Poisson distribution, which makes Poisson Regression a good possibility. Poisson variables are a count of something over a constant amount of time, area, or another consistent length of observation. With a Poisson variable, you can calculate and assess a rate of occurrence
  • Use Poisson regression to model how changes in the independent variables are associated with changes in the counts
  • Poisson models are similar to logistic models because they use Maximum Likelihood Estimation and transform the dependent variable using the natural log
  • Poisson models can be suitable for rate data, where the rate is a count of events divided by a measure of that unit’s exposure (a consistent unit of observation)

Resources