Count Data Analysis is a statistical method used to analyze data that represents counts of events or occurrences. This type of data often follows a discrete distribution, meaning the values are whole numbers, such as the number of times an event happens within a specific time frame. Common examples include the number of customer purchases or the frequency of accidents in a given area. In Count Data Analysis, specialized models like the Poisson regression or Negative Binomial regression are often employed to account for the unique characteristics of count data. These models help researchers understand relationships between variables and make predictions based on the count outcomes, providing valuable insights in fields such as epidemiology and economics.