Given that the median is invulnerable to extreme values but the mean is not, the best strategy is to report both of these measures when describing data distributions. The mean and the median can, in fact, be compared to form a judgment about whether the data are normally distributed, positively skewed, or negatively skewed. In normal distributions, the mean and median will be approximately equal. Positively skewed distributions will have means markedly greater than their medians. This is because extremely high values in positively skewed distributions pull the mean up but do not affect the location of the median. Negatively skewed distributions, on the other hand, will have medians that are noticeably larger than their means because extremely low numbers tug the mean downward but do not alter the median’s value.
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