## [answered] A sales manager collected the following data on annual sale

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A sales manager collected the following data on annual sales for new

customer accounts and the number of years of experience for a sample of 10

salespersons. Click on the webfile logo to reference the data. Develop an estimated regression equation that can be used to predict annual

sales given the years of experience.

Compute b1 and b0 (to the nearest whole number).

Complete the estimated regression equation below.

Y^=

+

x

Use the estimated regression equation to predict annual sales for a

salesperson with 9 years of experience (to the nearest whole number). 2. The data from exercise 3 follow. The estimated regression equation is

Y^= 7.6 + .9x.

What is the value of the standard error of the estimate (to 2 decimals)?

What is the value of the t test statistic (to 2 decimals)?

What is the p-value?

Use the F test to test for a significant relationship. Use alpha= .05.

Compute the value of the F test statistic (to 2 decimals).

What is the p-value?

What is your conclusion? 3. The number of megapixels in a digital camera is one of the most

important factors in determining picture quality. But do digital cameras with

more megapixels cost more? The following data show the number of

megapixels and the price (\$) for ten digital cameras (Consumer Reports,

March 2009). Click on the webfile logo to reference the data. b. At the .05 level of significance, are the number of megapixels and the

price related? c. Would you feel comfortable using the estimated regression equation

developed in part (a) to predict the price of a digital camera given the

number of megapixels?

d. The Canon Power Shot S95 digital camera has 10 megapixels. Predict the

price of this camera using the estimated regression equation developed in

part (a). 4.The owner of Showtime Movie Theaters, Inc., would like to predict weekly

gross revenue as a function of advertising expenditures. Historical data for a

sample of eight weeks follow.

Weekly

Television

Newspaper

Gross Revenue

(\$1,000s)

(\$1,000s)

(\$1,000s)

96

5.0

1.5

90

2.0

2.0

95

4.0

1.5

92

2.5

2.5

96

3.0

3.3

94

3.5

2.3

94

2.5

4.2

98

3.0

2.5

a. Develop an estimated regression equation with the amount of

television advertising as the independent variable (to 1 decimal).

Revenue =

+

b. Develop an estimated regression equation with both television

(to 2 decimals).

Revenue =

+

c. Is the estimated regression equation coefficient for television

advertising expenditures the same in part (a) and in part (b)? d.Predict weekly gross revenue for a week when \$3.5 thousand is spent on

thousands 5. The owner of Showtime Movie Theaters, Inc., would like to predict weekly

gross revenue as a function of advertising expenditures. Historical data for a

sample of eight weeks follow. Weekly

Gross

Revenue

(\$1000s)

97

90

95

93

96

94

94

95 Televison

(\$1000s)

5

3

5

3.5

4

4.5

3.5

4 Newspaper

(\$1000s)

2.5

2

2.5

3.5

4.3

2.3

4.2

3.5 a. Use alpha= .01 to test the hypotheses for the model y = 0 + 1x1 + 2x2 + , where Compute the F test statistic (to 2 decimals).

What is the p-value?

What is your conclusion? b. Use alpha= .05 to test the significance of beta1. Compute the t test

statistic (to 2 decimals).

What is the p-value?

Should x1 be dropped from the model? c. Use alpha= .05 to test the significance of beta2. Compute the t test

statistic (to 2 decimals).

What is the p-value?

Should x2 be dropped from the model?

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