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 66 movies, 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=−1.254+1.3968Xi. 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?
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 66 movies, 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=−1.254+1.3968Xi. 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?
College Algebra (MindTap Course List)
12th Edition
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:R. David Gustafson, Jeff Hughes
Chapter8: Sequences, Series, And Probability
Section8.CR: Chapter Review
Problem 37E: Find the positive geometric mean between 4 and 64.
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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 66 movies, 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=−1.254+1.3968Xi.
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)
56.138
13.560
12.257
11.106
84.723
33.480
22.589
3.268
6.433
46.824
10.738
26.040
1.755
56.788
8.343
11.276
9.633
3.199
0.485
8.049
4.090
9.910
33.511
1.260
5.331
6.808
54.956
6.072
28.930
4.226
15.883
57.660
82.910
Opening Weekend
Box Office Gross
($millions)
31.512
4.357
0.431
22.872
103.404
60.085
16.342
10.069
5.435
38.068
19.225
12.047
0.467
145.697
14.933
6.696
4.407
5.744
1.127
3.839
4.823
5.622
98.909
6.773
14.265
16.495
49.551
5.703
16.258
10.236
9.014
38.286
173.057
Online Trailer
Views (millions)
8.365
36.463
2.492
42.796
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
(Smillions)
0.455
59.430
18.730
88.369
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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