In: Statistics and Probability
To test the relationship between gender and ratings of a promiscuous partner, a group of men and women was given a vignette describing a person of the opposite sex who was in a dating relationship with one, two, or three partners. Participants rated how positively they felt about the individual described in the vignette, with higher ratings indicating more positive feelings.
| Source of Variation | SS | df | MS | F | 
|---|---|---|---|---|
| Gender | 10 | |||
| Promiscuity | ||||
| Gender × Promiscuity | 146 | |||
| Error | 570 | 114 | ||
| Total | 816 | 
(a) Complete the F-table and make a decision to retain or reject the null hypothesis for each hypothesis test. (Assume experimentwise alpha equal to 0.05.)
| 
Source of Variation  | 
SS | df | MS | F | 
|---|---|---|---|---|
| Gender | 10 | |||
| Promiscuity | ||||
| Gender × Promiscuity  | 
146 | |||
| Error | 570 | 114 | ||
| Total | 816 | 
| Source of Variation  | 
SS | df | MS | F | 
|---|---|---|---|---|
| Gender | 10 | 1 | 10 | 2 | 
| Promiscuity | 90 | 2 | 45 | 9 | 
| Gender × Promiscuity  | 
146 | 2 | 73 | 14.6 | 
| Error | 570 | 114 | 5 | |
| Total | 816 | 119 | 
First we will calculate all df values.
df Gender = Number of levels of Gender - 1 = 2 - 1 = 1
df Promiscuity = Number of levels of Promiscuity - 1 = 3 - 1 = 2
df Gender x Promiscuity = df Gender x df Promiscuity = 1 * 2 = 2
df Total = df Gender + df Promiscuity + df Gender x Promiscuity + df Error
= 1 + 2 + 2 + 114 = 119
SS Promiscuity = SS Total - (SS Gender + SS Gender x Promiscuity + SS Error)
= 816 - (10 + 146 + 570)
= 90
MS Gender = SS Gender / df Gender = 10 / 1 = 10
MS Promiscuity = SS Promiscuity / df Promiscuity = 90 /2 = 45
MS Gender × Promiscuity = SS Gender × Promiscuity / df Gender × Promiscuity = 146 / 2 = 73
MS Error = SS Error / df Error = 570 / 114 = 5
F Gender = MS Gender / MS Error = 10 / 5 = 2
F Promiscuity = MS Promiscuity / MS Error = 45 / 5 = 9
F Gender × Promiscuity = MS Gender × Promiscuity / MS Error = 73 / 5 = 14.6
Critical value of F at 0.05 significance level and df = df Gender, df Error = 1, 9 is 5.12
Since the observed F (2) is less than the critical value, we fail to reject the null hypothesis H0 and conclude that there is no significant main effect of gender on ratings.
Critical value of F at 0.05 significance level and df = df Gender, df Error = 2, 9 is 4.26
Since the observed F (9) is greater than the critical value, we reject the null hypothesis H0 and conclude that there is significant main effect of Promiscuity on ratings.
Since the observed F (14.6) is greater than the critical value, we reject the null hypothesis H0 and conclude that there is significant interaction effect of Gender and Promiscuity on ratings.