Due to the high number of individual items (42 in total), the number of
individual t-tests utilized in the study was very high. After running the initial t-test
analysis, 12 individual items resulted in a p-value of under the usual .05 alpha value
level for significance. However, due to the high number of t-tests run preliminarily,
the researcher had to accommodate for multiplicity. Multiplicity problems arise
when too many individual statistical tests are run. A high number of repeated
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examinations of data would ostensibly lead to an increased likelihood that a
significant difference between groups will be found, however the reality is that, with
so many different tests on the data, researchers must remain more critical and
skeptical of the data.