The psychopathology of everyday art: a quantitative Study - World ...

have equal variances, the ratio of the two sample variances has a sampling distribution
called the 'F' distribution, that is, the ratio of sample variances or square of ratio of the
sample standard deviations. There are two values for degrees of freedom - for each
variance, the first relates to the numerator and the second to the denominator. If the two
standard deviations are markedly different, it is unlikely that the two samples come from
populations with the same variance. ANOVA assumes two conditions and tests are
discussed below:
1. Each of the groups must be a sample from a normal population.
2. The variances within groups must be equal.
In practice the analysis of variance gives good results even if the normality assumption
doesn't quite hold but because of the imbalance in the number of observations in each of
the groups, the equal variance assumption was important. Distributions of values for
each variable were computed using the SPSS EXAMINE procedure.
The analysis of variance test does not isolate particular differing groups: it can
only tell us whether there is a difference and not where the difference lies. For this a
multiple comparison test is used. Because there were no grounds for prior hypothesis,
a planned comparison would be inappropriate with an omnibus test such as Anova.
Having observed a statistically significant effect using the oneway procedure, the
RANGE subcommand (Duncan procedure) was used to compare each group with every
other group; significance levels are attached to those groups showing most difference.
The comparisons use t-tests applied between independent samples for each variable,
comparing each pair of means in turn.
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