Example #3: You could use Poisson regression to examine the number of people ahead of you in the queue at the Accident & Emergency (A&E) department of a hospital based on predictors such mode of arrival at A&E (ambulance or self check-in), the assessed severity of the injury during triage (mild, moderate, severe), time of day and day of the week.
Here, the "number of credit card repayment defaults" is the dependent variable, whereas "job status" and "gender" are nominal independent variables, and "annual salary", "age" and "unemployment levels in the country" are continuous independent variables. Example #2: You could use Poisson regression to examine the number of times people in Australia default on their credit card repayments in a five year period based on predictors such as job status (employed, unemployed), annual salary (in Australian dollars), age (in years), gender (male and female) and unemployment levels in the country (% unemployed).Here, the "number of suspensions" is the dependent variable, whereas "gender", "race", "language" and "disability status" are all nominal independent variables. Example #1: You could use Poisson regression to examine the number of students suspended by schools in Washington in the United States based on predictors such as gender (girls and boys), race (White, Black, Hispanic, Asian/Pacific Islander and American Indian/Alaska Native), language (English is their first language, English is not their first language) and disability status (disabled and non-disabled).Some examples where Poisson regression could be used are described below: The variables we are using to predict the value of the dependent variable are called the independent variables (or sometimes the predictor, explanatory or regressor variables). The variable we want to predict is called the dependent variable (or sometimes the response, outcome, target or criterion variable). Poisson regression is used to predict a dependent variable that consists of "count data" given one or more independent variables. Poisson Regression Analysis using SPSS Statistics Introduction
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