What
are extreme scores? They are scores far outside the norm for a variable or
population, leading to the conclusion that they are not part of your true
population and probably do not belong in your analyses. A common
operationalizing definition for extreme scores is +/-3 standard deviations
(SDs) from the mean.
Recall that standard normal distribution of a population has
68.26% of the population between +1 and -1 SD of the mean (see attached
diagram: 34.13% between 0 to +1 SD +
34.13% between 0 and -1 SD = 68.26%).
So 95.44% of the population should fall between 2 SD from
the mean (34.13% + 34.13% + 13.59% +13.59% = 95.44%), and 99.74% of the
population should fall within 3 SD of the mean. In other words, the probability of
randomly sampling an individual more than 3 SD from the mean in a normally
distributed is 0.26%, which gives good justification for considering scores
outside 3 SD as suspect. Our concern is that these scores are not part of the
population of interest in your study.
Next time we will consider how extreme scores affect
statistical analyses. Do you have an issue or a question that you would like me
to discuss in a future post? Would you like to be a guest writer? Send me your
ideas! leann.stadtlander@waldenu.edu
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