Key Terms 455Optimism/PessimismOptimist PessimistMean Performance Ratio1.041.021.000.980.960.940.92Sex of subject
Male
Female(c) Plot by Sex 3 Optim interaction(^8) To be fair to Seligman et al. (1990), I should say that this is not a result they appeared to have analyzed for, and
therefore not one they found. I built it in to illustrate a point.
Key Terms
Factors (Introduction)
Two-way factorial design (Introduction)
Factorial design (Introduction)
Repeated-measures design
(Introduction)
Interaction (Introduction)
2 3 5 factorial (Introduction)
Cell (Introduction)
Main effect (13.1)
Simple effect (13.1)
SScells(13.1)
Disordinal interactions (13.3)
Ordinal interaction (13.3)
Crossed (13.8)
Random factor (13.8)
Nested design (13.8)
Random design (13.8)
Hierarchical models (13.8)
Mixed models (13.8)
Crossed experimental design (13.8)
Expected mean squares (13.8)
Partial effect (13.9)
Unbalanced design (13.9)
Unweighted means (13.11)
Equally weighted means (13.11)
First-order interactions (13.12)
Second-order interaction (13.12)
Simple main effects (13.12)
Simple interaction effect (13.12)
From the SPSS computer output you can see that there is a significant effect due to the
attributional style, with Optimists showing slightly improved performance after a perceived
failure, and pessimists doing worse. The difference in means may appear to be small, but
when you consider how close a race of this type usually is, even a tiny difference is impor-
tant. You can also see that there is a Optim 3 Sex interaction. Looking at the means we see
that there is almost no difference between Optimistic males and females, but this is not true
of pessimists. Pessimistic males appear in these data to be much more affected by a perceived
loss than are females. This Optim 3 Sex interaction is plotted as a bar chart following the
summary table. This plot has collapsed across Event, because that variable had no effect.^8
Table 13.17 (continued)