Sample Size and Power (B)
If no consideration is given to the concepts of effect
size and power, the researcher may end up very much in the dark as to
whether (1) a fail to reject decision is attributable to a trivial (or
zero) deviation from Ho or is attributable
to the test's insensitivity to detect important non-null cases due to
a small sample size, or (2) a reject decision is attributable to Ho
being false by a nontrivial amount or is attributable to an unimportant
non-null case being labeled significant simply because
the sample size was so large. In Excerpts 8.14 and 8.15 [not shown here],
we see examples of how murky results can be produced when the six-step
approach to hypothesis testing is used. In Excerpt 8.14, the researcher
tells us, in essence, that the statistically insignificant results may
have been caused by insufficient power. In Excerpt 8.15, we see a researcher
who obtained statistically significant results but admits, in essence,
that the initial findings may have been caused by an overly large sample
size making the statistical tests too sensitive.
(From Chapter 8, p. 217)
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