#16 in chapter 10 . Sinclair and Kunda (2000) tested the idea that, if you want

Question

#16 in chapter 10

. Sinclair and Kunda (2000) tested the idea that, if you want to think well of someone (for example, because he or she has said positive things about you), you are less influenced by the normal stereotypes when evaluating them. Participants filled out a questionnaire on their social skills, then either a male or female “manager in training” gave them feedback, rigged so that half the participants were given positive feedback and half, negative feedback. Finally, the participants rated the managers for their skill at evaluating them. The question was whether the usual tendency to stereotype women as less skillful managers would be undermined when people got positive ratings. Here are the results:

Participants’ ratings of the manager’s skill at evaluating them were analyzed with a 2 (feedback)×2×2 (manager gender) ANOVA. Managers who had provided positive feedback (M=9.08)(M=9.08) were rated more than were managers who had provided negative feedback (M=7.46),F(1,46)=19.44,p<.0001.(M=7.46),F(1,46)=19.44,p<.0001. However, as may be seen in Figure [10–15], the effect was qualified by a significant interaction, F(1,46)=4.71,p<.05.F(1,46)=4.71,p<.05. (pp. 1335–1336)

Figure 10-15

Participants’ ratings of the manager’s skill at evaluating them as a function of feedback favorability and the manager’s gender (Study 2).

Describe the meaning of these results to a person who understands one-way analysis of variance but is completely unfamiliar with factorial designs or the two-way analysis of variance.

Explanation / Answer

The dependent variable is manger's skill and the independent variables are feedback favourability and manager's gender. Two way ANOVA tests for three cases namely:-

Is there a significant difference in the proportion of people who ranked manager's skill in terms of variable 1(feedback favourability)?

Is there a significant difference in the proportion of people who ranked the manager's ability in terms of manager's gender(variable 2)?

is there any correlation between the two independent variables?

Thus, the first two cases are one-way ANOVA itself and the last test is one extra to evaluate any correlation between the variables. Two-way ANOVA does all these tests simultaneously.

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