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A consumer products company wants to measure the effectiveness of different types of advertising media in the promotion of its products. Specially, two types of advertising media are to be considered: radio and television advertising and newspaper advertising (including the cost of discount coupons). A sample of 22 cities with approximately equal population is selected for study during a test period of one month. Each city is allocated a specific expenditure level both for radio and television advertising and for newspaper advertising. The sales of the product (in thousands of dollars) and also the levels of media expenditure (in thousands of dollars) during the test month are recorded, with the data set ADVERTISE.XLS. Using EXCEL or PHStat2, answer the following:

Sales

Radio

Newspaper

973

0

40

1119

0

40

875

25

25

625

25

25

910

30

30

971

30

30

931

35

35

1177

35

35

882

40

25

982

40

25

1628

45

45

1577

45

45

1044

50

0

914

50

0

1329

55

25

1330

55

25

1405

60

30

1436

60

30

1521

65

35

1741

65

35

1866

70

40

1717

70

40

a) State the multiple regression equation.

b) Interpret the meaning of the slopes b1 and b2 in this problem.

c) Interpret the meaning of the regression coefficient b0 in this problem.

d) Predict the average sales for a city in which radio and television advertising is $20,000 and newspaper advertising is $20,000.

e) Set up a 95% confidence interval estimate for the average sales for cities in which radio and television advertising is $20,000 and newspaper advertising is $20,000.

f) Set up a 95% confidence interval estimate for the sales for an individual city in which radio and television advertising is $20,000 and newspaper advertising is $20,000.

g) Determine whether there is a significant relationship between sales and the two independent variables (radio advertising and newspaper advertising) at the 0.05 level of significance.

h) Interpret the meaning of the p-value.

i) Determine the coefficient of multiple determination, r2.

j) Determine the adjusted r2.

k) Perform a residual analysis on your results and determine the adequacy of the fit of the model.

l) Set up a 95% confidence interval estimate of the population slope between sales and radio and television advertising.

m) At the 0.05 level of significance, determine whether each explanatory variable makes a significant contribution to the regression model. On the basis of these results, indicate the independent variables that should be included in this model.

n) Compute the coefficients of partial determination, r2Y1.2.and r2Y2.1.and interpret their meaning.

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