A car 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 accompanying regression output was developed based on a random sample of employees. Complete parts a through d.

Column1 df SS Regression 1 75.319214 Residual 23 212.000786 Total 24 287.32 Coefficients Standard Error Intercept 7.476924 1.071329 Slope 0.577044 0.201865

a. Predict the sales next month for an employee with 4 years of experience.

The predicted sales is ---- cars.

(Type an integer or decimal rounded to one decimal place asneeded.)

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

The coefficient of determination is------.

(Type an integer or decimal rounded to three decimal places asneeded.)

Therefore, about ------ of the variation in ----------is explained by the ---------------.

(Type an integer or decimal rounded to one decimal place asneeded.)

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

=0.10?

The hypotheses for this test are

Upper H 0 : rho squared equals 0 and Upper H 1 :-----------

The test statistic is ------.

(Type an integer or decimal rounded to two decimal places asneeded.)

The p-value is-------.

(Type an integer or decimal rounded to three decimal places asneeded.)

At the

0.10 level of significance, reject/ fail to reject --------- the null hypothesis. There ---- sufficient evidence to conclude that the model is useful for making predictions.

d. Construct a 90% confidence interval around the sample slope and interpret its meaning. The confidence interval is

(-----,------).

(Type an integer or decimal rounded to three decimal places asneeded.)

One can be 90% confident that---------------is/are between the bounds of the confidence interval. Because this interval does not include ------------

zero, there is evidence to conclude that there----- linear relationship between the monthly sales and the sales experience of the employee.