Problem 2. (18 points I asked you to imagine that I worked for a record company and

that my boss was interested in predicting record sales from advertising. Before a record is

released, the executive notes the amount spent on advertising, the number of times the

record is played on radio the week before release, and the attractiveness of the band. He

does this for 200 different records (each made by a different band). Attractiveness was

measured by asking a random sample of the target audience to rate the attractiveness of

each band on a scale from 0 (hideous potato-heads) to 10 (gorgeous sex objects). The

mode attractiveness given by the sample was used in the regression (because he was

interested in what the majority of people thought, rather than the average of people's

opinions).

Copy and paste the data below into SPSS. (note the data appear out of line but they are

tab delimited for easy pasting into spss). Make sure after you paste the variables into spss

that they all remain scale and numeric (see data view)

Sales adverts airplay attract

330 10.26 43 10

120 985.69 28 7

360 1445.56 35 7

270 1188.19 33 7

220 574.51 44 5

170 568.95 19 5

70 471.81 20 1

210 537.35 22 9

200 514.07 21 7

300 174.09 40 7

290 1720.81 32 7

70 611.48 20 2

150 251.19 24 8

190 97.97 38 6

240 406.81 24 7

100 265.40 25 5

250 1323.29 35 5

210 196.65 36 8

280 1326.60 27 8

230 1380.69 33 8

210 792.35 33 7

230 957.17 28 6

320 1789.66 30 9

210 656.14 34 7

230 613.70 49 7

250 313.36 40 8

60 336.51 20 4

330 1544.90 42 7

150 68.95 35 8

150 785.69 8 6

180 125.63 49 7

80 377.93 19 8

180 217.99 42 6

130 759.86 6 7

320 1163.44 36 6

280 842.96 32 7

200 125.18 28 6

130 236.60 25 8

190 669.81 34 8

150 612.23 21 6

230 922.02 34 7

310 50.00 63 7

340 2000.00 31 7

240 1054.03 25 7

180 385.05 42 7

220 1507.97 37 7

40 102.57 25 8

190 204.57 26 7

290 1170.92 39 7

340 689.55 46 7

250 784.22 36 6

190 405.91 12 4

120 179.78 2 8

230 607.26 29 8

190 1542.33 33 8

210 1112.47 28 7

170 856.99 10 6

310 836.33 38 7

90 236.91 19 4

140 1077.86 13 6

300 579.32 30 7

340 1500.00 38 8

170 731.36 22 8

100 25.69 23 6

200 391.75 22 9

80 234.00 20 7

100 275.70 18 6

70 56.90 37 7

50 255.12 16 8

240 566.50 32 8

160 102.57 26 5

290 250.57 53 9

140 68.59 28 7

210 642.79 32 7

300 1500.00 24 7

230 102.56 37 6

280 756.98 30 8

160 51.23 19 7

200 644.15 47 6

110 15.31 22 5

110 243.24 10 8

70 256.89 1 4

100 22.46 1 6

190 45.69 39 6

70 724.94 8 5

360 1126.46 38 7

360 1985.12 35 5

300 1837.52 40 5

120 135.99 22 7

150 237.70 27 8

220 976.64 31 6

280 1452.69 19 7

300 1600.00 24 9

140 268.60 1 7

290 900.89 38 8

180 982.06 26 6

140 201.36 11 6

210 746.02 34 6

250 1132.88 55 7

250 1000.00 5 7

120 75.90 34 6

290 1351.25 37 9

60 202.71 13 8

140 365.99 23 6

290 305.27 54 6

160 263.27 18 7

100 513.69 2 7

160 152.61 11 6

150 35.99 30 8

140 102.57 22 7

230 215.37 36 6

230 426.78 37 8

30 507.77 9 3

80 233.29 2 7

190 1035.43 12 8

90 102.64 5 9

120 526.14 14 7

150 624.54 20 5

230 912.35 57 6

150 215.99 19 8

210 561.96 35 7

180 474.76 22 5

140 231.52 16 7

360 678.60 53 7

10 70.92 4 6

240 1567.55 29 6

270 263.60 43 7

290 1423.57 26 7

220 715.68 28 7

230 777.24 37 8

220 509.43 32 5

240 964.11 34 7

260 583.63 30 7

170 923.37 15 7

130 344.39 23 7

270 1095.58 31 8

140 100.03 21 5

60 30.43 28 1

210 1080.34 18 7

210 799.90 28 7

240 1071.75 37 8

210 893.36 26 6

200 283.16 30 8

140 917.02 10 7

90 234.57 21 7

120 456.90 18 9

100 206.97 14 7

360 1294.10 38 7

180 826.86 36 6

150 564.16 32 7

110 192.61 9 5

90 10.65 39 5

160 45.69 24 7

230 42.57 45 7

40 20.46 13 8

60 635.19 17 6

230 1002.27 32 7

230 1177.05 23 6

120 507.64 0 6

150 215.69 35 5

120 526.48 26 6

60 26.90 19 6

280 883.88 26 7

120 9.10 53 8

230 103.57 29 8

230 169.58 28 7

40 429.50 17 6

140 223.64 26 8

360 145.59 42 8

210 985.97 17 6

260 500.92 36 8

250 226.65 45 7

200 1051.17 20 7

150 68.09 15 7

250 1547.16 28 8

100 393.77 27 6

260 804.28 17 8

210 801.58 32 8

290 450.56 46 9

220 26.60 47 8

70 179.06 19 1

110 345.69 22 8

250 295.84 55 9

320 2271.86 31 5

300 1134.58 39 8

180 601.43 21 6

180 45.30 36 6

200 759.52 21 7

320 832.87 44 7

140 56.89 27 7

100 709.40 16 6

120 56.90 33 6

230 767.13 33 8

150 503.17 21 7

250 700.93 35 9

190 910.85 26 7

240 888.57 14 6

250 800.62 34 6

230 1500.00 11 8

110 785.69 20 9

1. C omplete a simultaneous multiple regression using adverts, airplay and attractiveness

to predict sales. Write the full regression equation below.

2. What percent of the variance is uniquely accounted for by

adverts?________________

3. What percent of the variance is uniquely accounted for by

airplay?________________

4. What percent of the variance is uniquely accounted for by

attractiveness?________________

5. With all other variables held constant, for each unit increase of attractiveness, how

much do sales change?_____________

6. With all other variables held constant, for each unit increase of advertising, how

much do sales change?_____________

7. With all other variables held constant, for each unit increase of airplay, how much

do sales change?____________

8. With all other variables held constant, for each SD increase of attractiveness, how

much do sales change?_____________

9. With all other variables held constant, for each SD unit increase of advertising,

how much do sales change?_____________

10. With all other variables held constant, for each unit SD increase of airplay, how

much do sales change?_____________

11. What number is the denominator of the t ratio for testing the effect of

attractiveness_________?

12. What number is the denominator of the t ratio for testing the effect of

advertising_.________?

13. What number is the denominator of the t ratio for testing the effect of amount of

airplay_________?

14. What number indicates the error in measurement?_______

15. Do you have problems with multi-colinnearity? Provide 3 reasons to support your

position.