Count data model
Poisson regression is a form of regression used to model the count of data in contingency tables. For example, counting the number of births or the number of wins in a series of soccer matches. Poisson regression assumes that the response variable Y has a Poisson distribution, and that the logarithm of its expected value can be modelled by a linear combination of unknown parameters. Poisson regression is sometimes also known as a log-linear model, especially when it is used to model contingency tables.
Poisson distributions
A distribution tells us how measures of a certain variable are distributed among the various possible values. Each distribution is characterized by an average value and a variance, which adjusts the uncertainty of the measurements obtained. Poisson's distribution, also known as rare event law, is a very useful type of distribution when dealing with extremely rare events, which occur with a well-defined temporal mean. It is an approximation of the binomial...
