In: Math
SS |
df |
MS |
F |
|
Rating |
455 |
|||
Season |
192.5 |
|||
Interaction |
140 |
Required Formulae:
DFrating = number of ratings - 1
DFseason = number of season - 1
DFinteraction = DFrating * DFseason
SS | df | MS | F | F-critical | |
Rating | 455 | 5 - 1 = 4 | |||
Season | 192.5 | 2 - 1 = 1 | |||
Interaction | 140 | 4 * 1 = 4 | |||
Error | 1050 | 69 - 4 - 1 - 4 = 60 | |||
Total | 1837.5 | 70 - 1 = 69 |
a) ANOVA table:
SS | df | MS | F | |
Rating | 455 | 4 | 113.75 | 6.5 |
Season | 192.5 | 1 | 192.5 | 11 |
Interaction | 140 | 4 | 35 | 2 |
Error | 1050 | 60 | 17.5 | |
Interaction | 1837.5 | 69 |
b) critical value:
Critical value for rating is 2.525.
Critical value for Season is 4.001
Critical value for interaction is 2.525
c)
i) Rating:
6.5 > 2.525
Therefore, we reject null hypothesis.
There is sufficient evidence to conclude that box office revenue vary with ratings of the movie.
ii) Season:
11 > 4.001
Therefore, we reject null hypothesis.
There is sufficient evidence to conclude that box office revenue vary with season in which movie releases.
iii) Interaction:
2 < 2.525
Therefore, we fail to reject null hypothesis.
There is sufficient evidence to conclude that box office revenue does not vary with interaction of season and movie rating.