The resulting analysis is shown in

The resulting analysis is shown in SPSS Output 10.1. It might be a good idea to remind
yourself of the group means from Table 10.1. The first thing to notice is that just as in the
regression chapter, an ANOVA has been used to test the overall fit of the model. This test
is significant, F(2, 12) = 5.12, p < .05. Given that our model represents the group differences,
this ANOVA tells us that using group means to predict scores is significantly better
than using the overall mean: in other words, the group means are significantly different.
In terms of the regression coefficients, bs, the constant is equal to the mean of the base
category (the placebo group). The regression coefficient for the first dummy variable
(b2) is equal to the difference between the means of the high-dose group and the placebo
group (5.0 − 2.2 = 2.8). Finally, the regression coefficient for the second dummy variable
(b1) is equal to the difference between the means of the low-dose group and the placebo
group (3.2 − 2.2 = 1). This analysis demonstrates how the regression model represents
the three-group situation. We can see from the significance values of the t-tests that the
difference between the high-dose group and the placebo group (b2) is significant because
p < .05. The difference between the low-dose and the placebo group is not, however,
significant (p = .282).
A