A pedagogical example of a negatively skewed distribution is a dataset of self-report happiness ratings on a $$1$$-to-$$10$$-point scale with a mean of $$8.25$$ and a standard deviation of $$1.14$$. In this scenario, the negative skew indicates that the vast majority of participants rated themselves fairly high on the happiness scale (clustering near the top), with only a small number of participants rating themselves noticeably lower (creating the longer tail toward the lower end).

Example of a Negatively Skewed Distribution

Which of the following best describes the shape of a negatively skewed distribution?

A negatively skewed distribution is an asymmetrical shape of a data distribution where the majority of scores are clustered toward the higher end of the scale, creating a prominent peak on the right, while a relatively long tail trails off toward the lower end of the scale on the left.

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A skewed distribution is an asymmetrical shape of a data distribution where scores cluster heavily toward one end of the scale, creating a prominent peak, while a relatively long tail trails off toward the opposite end.

Skewed Distribution

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KPU Research Methods in Psychology - 4th American Edition

A positively skewed distribution is an asymmetrical shape where the peak of the scores is shifted toward the lower end of its range, resulting in a relatively long positive tail that trails off toward the higher values.

Positively Skewed Distribution

A key characteristic of the mean is its high sensitivity to extreme scores, or outliers. In highly skewed distributions, the mean is pulled away from the median in the direction of the skew (the longer tail). Because extreme scores heavily influence its value, the mean may cease to be an accurate representation of the typical score in such datasets, leading researchers to often prefer the median for skewed distributions.

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