o begin our analysis, we need to divide the data into a training and test data set. The training data set has 70% of the data and is used to build the decision tree model and the test dataset has the remaining 30% of the data and is used to evaluate the accuracy of the model. We will then take the training data set and run the general linear model or glm function to build the model. A general linear model is a type of linear regression modeling that allows for variables that have error distribution models that do not have a normal distribution. To review the data after running the glm function we use the print function and the results are in figure 3 below