Poisson Regressionoverview how to example data see also
Poisson RegressionStat > Regression > Poisson Regression > Fit Poisson Model
Use Poisson Regression when the response variable describes the number of times an event occurs in a finite observation space. Use this feature to for the following purposes:
The default model contains the predictors that you enter in Continuous predictors and Categorical predictors. If you want to add interaction and polynomial terms, use the tools in the Model dialog box.
Minitab stores the last model that you fit. You can use the stored model to quickly generate predictions, contour plots, surface plots, overlaid contour plots, and optimized responses.
Response: Select the Poisson variable that you want to explain or predict with the predictors (X). The response is also called the Y variable.
Frequency (optional): If the response data are in two columns - one column that contains the response values and one column that contains their frequencies - enter the column that contains the frequencies.
Continuous predictors: Select the continuous variables that explain changes in the response. The predictor is also called the X variable.
Categorical predictors: Select the categorical classifications or group assignments, such as type of raw material, that explains changes in the response. The predictor is also called the X variable.