A consumer products company wants to measure the effectiveness of different types of advertising media in the promotion of its products. Specifically, 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 for both radio and television advertising and newspaper advertising. The sales of the product (in thousands of dollars) and 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 (000s) | Radio (000s) | Newspaper (000s) |
|--------------|--------------|------------------|
| 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 |

Tasks:

a) State the multiple regression equation.

b) Interpret the meaning of the slopes \( b_1 \) and \( b_2 \) in this problem.

c) Interpret the meaning of the regression coefficient \( b_0 \) in this problem.

d) Predict the average sales for a city where 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 where 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 where 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, \( r^2 \).

j) Determine the adjusted \( r^2 \).

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. Indicate the independent variables that should be included in this model based on these results.

n) Compute the coefficients of partial determination, \( r^2_{Y1.2} \) and \( r^2_{Y2.1} \), and interpret their meaning.