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Distribution is even when it's equal, uneven when it's not. For example, the United States population is distributed unevenly. The 2010 census showed some states have a much higher population per square mile than others.
A further characterization of the data includes skewness and kurtosis. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the center point.Kurtosis is a measure of whether the data are peaked or flat relative to a normal distribution.That is, data sets with high kurtosis tend to have a distinct peak near the mean, decline rather rapidly, and have heavy tails. Data sets with low kurtosis tend to have a flat top near the mean rather than a sharp peak.he above formula for skewness is referred to as the Fisher-Pearson coefficient of skewness. Many software programs actually compute the adjusted Fisher-Pearson coefficient of skewness. The skewness for a normal distribution is zero, and any symmetric data should have a skewness near zero.