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 | ![]()  | 
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| Season | 192.5 | 2 - 1 = 1 | ![]()  | 
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| Interaction | 140 | 4 * 1 = 4 | ![]()  | 
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| 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.