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. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 The predicted sales is 8.6 cars. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is (Type an integer or decimal rounded to three decimal places as needed.)

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...

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.


	ANOVA df	SS
Regression	1	79.909407
Residual	23	261.210593
Total	24	341.12

	Coefficients	Standard Error
Intercept	7.271539	1.229763
Slope	0.539854

The predicted sales is 8.6 cars.

Compute the coefficient of determination and interpret its meaning.

The coefficient of determination is

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

Jun 06, 2022

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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...

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