Poisson and Negative Binomial Regression for Count Data

by Karen

Ever discover that your data are not normally distributed, no matter what transformation you try? It may be that they follow another distribution altogether.

Although they are numerical, discrete count data often follow a Poisson or Negative Binomial distribution, not a normal one.

Examples of discrete counts include:

  • Number of tagged fish that return to a reef each month
  • Number of months of unemployment
  • Number of arrests in a neighborhood

This webinar will give you an overview of Poisson and Negative Binomial regression models, including:

  • how these regression models differ from Ordinary Linear Regression
  • the type of data for which each is appropriate
  • how to interpret the output from each

The recording is free, but you must register.

As a bonus, you will also receive our monthly newsletter, StatWise.

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{ 1 comment… read it below or add one }

Konstantinos Angelis December 2, 2011 at 4:32 pm

Very very nice and helpful initiative, especially for biostatistician students as me!

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