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Sometimes, we want to look at more
than two groups of data and compare them. We want to see if more than two
groups of data are different. While we could use T-tests to compare the
means from two different groups of data, but we need a different kind of
test when comparing three or more groups.
We can use a 1-Way ANOVA test to
compare three or more groups or conditions in an experiment. A 1-Way ANOVA
can help you find out if the means for each group / condition are
significantly different from one another or if they are relatively the same.
If the means are significantly different, you can say that the variable
being manipulated, your Independent Variable (IV), had an effect on
the variable being measured, your Dependent Variable (DV). You will
probably be asked to do two popular types of 1-Way ANOVA tests in SPSS so we
will talk about each.
ANalysis Of Variance.
With ANOVA, we analyze and compare the variability of scores between
conditions and within conditions. This helps us find out if the IV had a
significant effect on the DV.
Because we use this test to analyze
data from experiments that have only one IV. If we were analyzing
data from experiments with more than one IV, we would need to use a
different test.
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This type of test is used to compare
more three or more groups of participants that are not related in any way.
The groups of participants are independent from one another. So,
participants in one group have no relationship to participants in the other
groups.
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This type of test used to compare
three or more groups of participants that are related in some way. There are
so many ways that participants in three or more groups can be related. One
of the most common ways is that participants in the first group are the same
as participants in the other groups. This is called a repeated measures
design. For this reason, some people call the 1-Way Within Subjects ANOVA a
1-Way Repeated Measures ANOVA.
A second way is that participants in
the first group are genetically related to participants in the other groups.
For example, a pair of triplets could be divided up so one triplet
participated with the first group, a second triplet participated with the
second group and a third triplet participate with a third group. A third way
is if participants in one group are matched with participants in the other
groups by some attribute. For example, if a participant in the first group
rates low on intelligence, researchers might try to find a participant for
each of the other groups who also rates low on intelligence.
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