RESEARCH METHOD COHEN ok

550 QUANTITATIVE DATA ANALYSIS
urban, i.e. the differences relate to geographical
location rather than age group in the school. The
Tukey test helps us to locate exactly where the
similarities and differences between groups lie. It
places the means into homogeneous subgroups, so
that we can see which means are close together
but different from other groups of means.
Analysis of variance here tells us that there
are or are not statistically significant differences
between groups; the Tukey test indicates where
these differences lie, if they exist. We advise
using the two tests together. Of course, as with
the t-test, it is sometimes equally important if
we do not find a difference between groups as
if we do find a difference. For example, if we
were to find that there was no difference between
four groups (parents, teachers, students and school
governors/leaders) on a particular issue, say the
move towards increased science teaching, then
this would give us greater grounds for thinking
that a proposed innovation – the introduction
of increased science teaching – would stand a
greater chance of success than if there had been
statistically significant differences between the
groups. Finding no difference can be as important
as finding a difference.
In reporting analysis of variance and the Tukey
test one could use a form of words thus:
Analysis of variance found that there was a
statistically significant difference between rural
and urban schools (F = 8.976, ρ