A Step by Step Guide for SPSS and Exercise Studies

Statistical tests 83
Figure 24
residuals against the predicted values (to save these values in the data file,
use the Save option below). If this assumption is met, there should be no
specific pattern in the spread of the residuals. However, in Figure 25, there
seems to be a pattern as the variability of the residuals decreases with
increasing predicted values (i.e., heteroscedasticity). Usually, the literature
reports cases where the variability of the residuals increases at larger
predicted values. An alternative way to test this assumption is to re-run the
Univariate analysis using the residuals as the dependent variable. A nonsignificant
Levene test will signify that the assumption of homogeneous
variances cannot be rejected. Heteroscedasticity reduces the power of
ANOVA to discover significant results (i.e., Type II error).
3. The relationship between the residuals and the predicted values of the
dependent variable should be linear. However, inspection of Figure 25
reveals that this relationship is non-linear. Non-linearity also reduces the
power of ANOVA.
4. The residuals are independent. This assumption requires that the score of
one participant is not related in any way to the score of another participant.
This assumption is violated when the order in which participants are
assessed may influence their performance. For example, imagine an
inexperienced researcher who is able to provide better instructions to the
participants who join his/her experiment later on rather than earlier. Better