This course is for those who analyze the number of occurrences of an event or the rate of occurrence of an event as a function of some predictor variables. For example, the rate of insurance claims, colony counts for bacteria or viruses, the number of equipment failures, and the incidence of disease can be modeled using Poisson regression models.
This course includes practice data and exercises.
Learn how to
 fit Poisson regression models for discrete counts and rates
 assess the models for overdispersion
 fit negative binomial regression models
 fit zeroinflated Poisson models and zeroinflated negative binomial models
 perform model diagnostics with ODS graphics.
Who should attend
Biostatisticians, epidemiologists, social scientists, physical scientists, and business analysts
Formats available  Duration   
eLearning: 
3.5 hours/180 day license 

Before attending this course, you should be able to
 execute SAS programs and create SAS data sets
 fit and interpret linear regression and logistic regression models.
You can obtain this experience by completing the SAS Programming 1: Essentials and Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression courses.
This course addresses SAS/STAT software.