A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−0.372+1.3802Xi. Complete parts (a) through (d). a. Determine the coefficient of determination, r2, and interpret its meaning. b. Determine the standard error of the estimate. c. How useful do you think this regression model is for predicting opening weekend box office gross? d. Can you think of other variables that might explain the variation in opening weekend box office gross?
A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−0.372+1.3802Xi. Complete parts (a) through (d). a. Determine the coefficient of determination, r2, and interpret its meaning. b. Determine the standard error of the estimate. c. How useful do you think this regression model is for predicting opening weekend box office gross? d. Can you think of other variables that might explain the variation in opening weekend box office gross?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−0.372+1.3802Xi.
Complete parts (a) through (d).
a. Determine the coefficient of determination, r2, and interpret its meaning.
b. Determine the standard error of the estimate.
c. How useful do you think this regression model is for predicting opening weekend box office gross?
d. Can you think of other variables that might explain the variation in opening weekend box office gross?
Transcribed Image Text:Online Trailer
Views (millions)
57.001
10.582
12.803
10.136
85.661
34.667
22.859
7.979
1.024
47.203
10.454
28.018
7.171
57.758
7.663
10.810
8.279
1.262
0.645
2.979
8.347
6.104
30.746
1.953
1.138
10.270
54.329
1.530
29.231
7.845
11.899
60.723
82.423
Opening Weekend
Box Office Gross
($millions)
32.618
8.425
2.461
23.160
104.670
58.987
18.934
13.157
3.551
39.466
20.769
18.416
3.246
149.360
10.719
7.497
1.251
5.039
1.597
1.937
6.451
5.254
101.968
0.869
15.357
14.209
46.466
5.521
17.099
9.363
12.450
37.744
174.927
Online Trailer
Views (millions)
4.255
35.016
0.335
45.410
4.989
6.630
0.942
2.258
11.327
8.966
15.177
13.714
31.231
52.612
16.235
6.884
11.698
2.827
23.075
12.606
0.826
27.536
7.273
3.323
4.267
3.790
7.597
12.912
7.067
5.020
7.739
16.795
7.643
Opening Weekend
Box Office Gross
($millions)
4.875
57.252
19.169
91.014
4.690
33.377
3.705
1.513
18.470
12.202
4.357
30.436
53.003
46.607
13.003
3.776
18.223
3.471
13.602
40.011
1.385
20.130
3.404
1.207
10.951
8.344
11.614
13.501
5.106
1.985
22.800
13.689
2.080
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