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   1. Predict the sales next month for an employee with 2.5 years of experience.   The predicted sales is 8.6 cars.   2. Compute the coefficient of determination and interpret its meaning.   The coefficient of determination is 0.234.   3. 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​?   The test statistic is ​(Type an integer or decimal rounded to two decimal places as​ needed.)

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Author:Amos Gilat
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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 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
 
1. Predict the sales next month for an employee with 2.5 years of experience.
 
The predicted sales is 8.6 cars.
 
2. Compute the coefficient of determination and interpret its meaning.
 
The coefficient of determination is 0.234.
 
3. 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​?
 
The test statistic is
​(Type an integer or decimal rounded to two decimal places as​ needed.)
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