Statistical Significance vs. Practical
Significance (B)
Earlier in this chapter, you saw how researchers can
do certain things in an effort to see whether a statistically significant
finding is also meaningful in a practical sense. Unfortunately, many researchers
do not rely on computed effect size indices, strength-of-association measures,
or power analyses to help them avoid the mistake of "making a mountain
out of a molehill." They simply use the six-step version of hypothesis
testing and then get excited if the results are statistically significant.
Having results turn out to be statistically significant
can cause researchers to go into a trance in which they willing allow
"the tail to wag the dog." Consider, for example, Excerpt 11.34
[not shown here]. In this instance, the "tail" was the presence
of a statistically significant difference between the two means, and the
"dog" was the researchers' assessment as to whether this difference
was meaningful in a practical sense.
When the researchers stated that "despite the small
difference in means, there was a significant difference," they imply
that their statistical analysis has come along and magically transformed
a "molehill" of a mean difference into a "mountain"
that deserves others' attention. Had they not been blinded by the allure
of statistical significance, the researchers would have focused on the
"small difference" and not the "significant difference,"
and perhaps they would have said "although there was a statistically
significant difference between the means, the mean difference was small."
(From Chapter 11, p. 318)
|