Question: A Buick dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based

A Buick dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee’s number of years of sales experience. The following regression output was developed based on a random sample of employees.

Anova df Regression Residual Total 23 24 84.72068376 243.1193162 327.84 Coefficients Standard

a. Predict the sales next month for an employee with 3.5 years of sales experience.

b. Compute the coefficient of determination and interpret its meaning.

c. Do the sample data provide evidence that the model is useful for predicting average monthly sales for employees based on their sales experience using α = 0.05?

d. Construct a 95% confidence interval around the sample slope and interpret its meaning.

Anova df Regression Residual Total 23 24 84.72068376 243.1193162 327.84 Coefficients Standard Error 7.069059829 1507676628 Experience 0.601709402 0.212538635

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