Mr. Kuku, a UM Flint graduate, working for an online retailer discovers that onl

Question

Mr. Kuku, a UM Flint graduate, working for an online retailer discovers that online sales of a certain product are related to the amount of dollars spent on Facebook ads. Kuku quickly builds a regression model to predict sales given the amount of money spent on Facebook ads. The data and the regression output from Excel are shown below.

Week

Sales (# of Units)

Facebook Ad Spending

1

1050

500

2

2100

1250

3

1345

950

4

900

450

5

1825

980

6

2240

1400

Regression output from Excel:

Regression Statistics

Multiple R

0.96

R Square

0.93

Adjusted R Square

0.91

Standard Error

165.69

Observations

6.00

Coefficients

Standard Error

t Stat

P-value

Intercept

285.38

189.85

1.50

0.21

Facebook Ad Spending

1.40

0.19

7.28

0.00

What is the expected sales if the company plans to spend 1500$ on Facebook ads? Please round your answer to 2 decimal places. Enter only a number in the space provided.

Week

Sales (# of Units)

Facebook Ad Spending

1

1050

500

2

2100

1250

3

1345

950

4

900

450

5

1825

980

6

2240

1400

Explanation / Answer

The regression equation is Yi =b0 +b1xi +ei

xi =the value of the independent variable for the ith value

Yi =the value of the dependent variable for the ith value

b0 =the population y intercept

b1=the population slope

ei =the error of prediction for the ith value

For the problem ,

xi , Facebook ad spending

Yi =the value of the dependent variable for the ith value

b0 =285.38

b1=1.40

ei = 0, because the y point (expected sales ) is on the regression line)

Expected sales =285.38 +1.40 (Facebook ad spending) + 0

For xi , Facebook ad spending =$ 1500

Expected sales =285.38 +1.40 (1500) + 0 =2385.38

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