Friday, April 27, 2018

Making Data Make Sense- Extreme Scores


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 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 population 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 I will post an updated blog index. 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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