Question
Online Trailer Views (millions) Opening Weekend Box Office Gross ($millions)
55.111 34.124
9.416 6.181
7.71 5.578
5.895 23.917
83.065 102.533
32.862 62.143
24.105 19.96
5.005 9.721
4.986 11.059
45.03 34.715
10.232 20.686
25.461 17.497
2.238 3.926
55.386 149.481
4.512 9.113
11.469 12.88
11.472 2.08
1.666 1.816
0.792 0.4
3.985 4.444
3.476 1.652
10.421 1.069
33.085 99.151
1.386 3.904
5.535 9.989
6.637 13.392
55.098 46.803
4.953 3.993
28.861 15.018
4.282 5.937
11.836 9.929
60.033 44.189
82.933 176.137
4.346 7.222
33.811 61.791
3.701 16.762
44.788 84.676
4.989 4.69
6.63 33.377
0.942 3.705
2.258 1.513
11.327 18.47
8.966 12.202
15.177 4.357
13.714 30.436
31.231 53.003
52.612 46.607
16.235 13.003
6.884 3.776
11.698 18.223
2.827 3.471
23.075 13.602
12.606 40.011
0.826 1.385
27.536 20.13
7.273 3.404
3.323 1.207
4.267 10.951
3.79 8.344
7.597 11.614
12.912 13.501
7.067 5.106
5.02 1.985
7.739 22.8
16.795 13.689
7.643 2.08

A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to usec. How useful do you think this regression model is for predicting movie weekend box office gross? O A. It is not useful for

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Answer #1

a)

The r**2 comes out to be 0.678.

The value of r**2 indicates that 67.8% of the variation in opening weekend box office gross can be explained by the variation in online trailer views.

b)

standard error = standard deviation / sqrt(n)

n = 66

The standard error comes out to be 4.139.

c)

The value of coefficient of determination comes out to be 0.678, which is closer to 1 more than 0.

Option B is the right answer here.

с D E F G H r r**2 S.D S.E А B 1 Online Trailer Views (millions) Opening Weekend Box Office Gross ($millions) 2 55.111 34.124

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