Analysis Of Poisson Regression Using Spss Statistics

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6. ANALYSIS OF POISSON REGRESSION USING SPSS STATISTICS 6.1. Introduction As we said earlier, Poisson regression is used to model dependent variable (consists of "count data") given one or more independent variables. Dependent variable also called the outcome, response or criterion variable is the variable that we want to predict. On the other hand, independent variables also called predictors, explanatory or regressed variables are variables used to predict the value of the dependent variable. 6.2. Examples of Poisson Regression Example 1. The number of people in line in front of you at the grocery store. Predictors may include the number of items currently offered at a special discounted price and whether a special event (e.g., a holiday, a big sporting event) is three or fewer days away. Example 2. The number of awards earned by students at one high school. Predictors of the number of awards earned include the type of program in which the student was enrolled (e.g., vocational, general or academic) and the score on their final exam in math. Example 3. The number of students who catch cold at one elementary school. Predictor of the number of sicknesses might be the average weekly temperature in the area where the students live. 6.3. Description of the Data For the purpose of illustration, we have simulated a data set for Example 3 above. In this example, num_of_sickness is the outcome variable and indicates the number of sicknesses reported weekly by students at an

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