The human resources department at a large company wants to develop a model to predict an employee’s job satisfaction from the number of hours of unpaid work per week the employee does, the employee’s age, and the employee’s income. We interpret the coefficient of multiple determination in the same way that we interpret the coefficient of determination for simple linear regression. The value of the coefficient of multiple determination is found on the regression summary table, which we learned how to generate in Excel in a previous section. The coefficient of multiple determination is the proportion of variation in the dependent variable that can be explained by the multiple regression model based on the independent variables. The coefficient of multiple determination, denoted R^2, in multiple regression is similar to the coefficient of determination in simple linear regression, except in multiple regression there is more than one independent variable. The coefficient of determination is a good way to measure how well the simple linear regression model fits the data. Previously, we learned about the coefficient of determination, r^2, for simple linear regression, which is the proportion of variation in the dependent variable that can be explained by the simple linear regression model based on the independent variable. Calculate and interpret the coefficient of multiple determination.
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