Outliers
If allowed to remain in a data set, outliers can create
skewness and in other ways create problems for the researcher. Accordingly,
the researchers who conducted the studies that appear in Excerpts 2.39-2.41
deserve credit for taking extra time to look for outliers before conducting
any additional data analyses. We should point out, however, that outliers
potentially can be of legitimate interest in and of themselves. Instead
of quickly tossing aside any outliers, researchers would be well advised
to investigate any "weird cases" within their data sets. Even
if the identified outliers have come about because of poorly understood
directions, erratic measuring devices, low motivation, or effort to disrupt
the study, researchers in these situations might well ask the simple question,"Why
did this occur?" More importantly, outliers that exist for other
reasons have the potential, if considered thoughtfully, to provide insights
into the genetic, psychological, and/or environmental factors that stand
behind extremely high or low scores.
(From Chapter 2, p. 51)
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