RESEARCH METHOD COHEN ok

MEASURES OF DIFFERENCE BETWEEN GROUPS AND MEANS 557
Box 24.61
Frequencies for variable one in the Friedman test
The course encouraged and stimulated your motivation and willingness to learn
Valid
Not at all Very little A little Quite a lot A very great deal Total Total
Frequency 1 13 64 79 32 189 191
Valid percent 0.5 6.9 33.9 41.8 16.9 100.0
Chapter 24
Box 24.62
Frequencies for variable two in the Friedman test
The course encouraged you to take responsibility for your own learning
Valid
Not at all Very little A little Quite a lot A very great deal Total Total
Frequency 1 9 64 85 30 189 191
Valid percent 0.5 4.8 33.9 45.0 15.9 100.0
(See http://www.routledge.com/textbooks/
9780415368780 – Chapter 24, file Manual
24.12.)
For more than two related samples (e.g. the same
group voting for three or more items, or the same
grouping voting at three points in time) the Friedman
test is applied. For example, in Boxes 24.61 to
24.63 are three variables (‘The course encouraged
and stimulated your motivation and willingness to
learn’, ‘The course encouraged you to take responsibility
for your own learning’ and ‘The teaching
and learning tasks and activities consolidate learning
through application’), all of which are voted
on by the same group. The frequencies are given. Is
there a statistically significant difference between
the groups in their voting
The Friedman test reports the mean rank and
then the significance level; in the examples
here the SPSS output has been reproduced
(Boxes 24.64 and 24.65).
Here one can see that, with a significance level
of 0.838 (greater than 0.05), the voting by the same
group on the three variables is not statistically
significantly different, i.e. the null hypothesis is
supported. The reporting of the results of the Friedman
test can follow that of the Kruskal-Wallis test.
For both the Kruskal-Wallis and the Friedman
tests, as with the Mann-Whitney and Wilcoxon
tests, not finding a statistically significant difference
between groups can be just as important
as finding a statistically significant difference between
them, as the former suggests that nominal
characteristics of the sample make no statistically
significant difference to the voting, i.e. the voting
is consistent, regardless of particular features of the
sample.
The k-sample slippage test from Conover
(1971), as an alternative to the Kruskal-
Wallis test, is set out in the accompanying
web site: see http://www.routledge.com/textbooks/
9780415368780 – Chapter 24, file 24.6.doc.
Several data sets for use with SPSS are included
on the accompanying web site, using fictitious
data, thus:
an SPSS data file on managing change:
http://www.routledge.com/textbooks/
9780415368780/, file ‘data file on change’