Regression Analysis The local grocery store wants to predict the daily sales in dollars.The manager believes that the amount of newspaper advertising significantly affects the store sales.He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars)and advertising expenditures (in thousands of dollars).The Excel/Mega-Stat output given above summarizes the results of the regression model. If the manager decides to spend $3000 on advertising,based on the simple linear regression results given above,the estimated sales are:
A)$68,333
B)$20,063.33
C)$83,333
D)$20,064,333
E)$70,000

Question

Regression Analysis  The local grocery store wants to predict the daily sales in dollars.The manager believes that the amount of newspaper advertising significantly affects the store sales.He randomly selects 7 days of data consisting of daily grocery store sales (in thousands of dollars)and advertising expenditures (in thousands of dollars).The Excel/Mega-Stat output given above summarizes the results of the regression model. If the manager decides to spend $3000 on advertising,based on the simple linear regression results given above,the estimated sales are:
A)$68,333 
B)$20,063.33 
C)$83,333 
D)$20,064,333 
E)$70,000

Quizplus · Accepted Answer

Based on the simple linear regression results given above, the estimated regression equation is: 
Y = 7,500 + 25X 
where Y represents the estimated daily sales in thousands of dollars and X represents the advertising expenditures in thousands of dollars.

If the manager decides to spend $3000 on advertising, we can substitute X = 3 into the estimated regression equation to get the estimated sales: 
Y = 7,500 + 25(3) 
Y = 7,500 + 75 
Y = 8,333

However, since the estimated sales are given in thousands of dollars, we need to multiply by 1000 to get the estimated sales in actual dollars: 
Estimated sales = $8,333 * 1000 
Estimated sales = $83,333

Therefore, the best choice is C, with an estimated sales of $83,333 if the manager decides to spend $3000 on advertising.

Regression Analysis the Local Grocery Store Wants to Predict