Machine Learning Resources

What is Skewness and Kurtosis?

Skewness measures the degree of symmetry present in a distribution. In a distribution with no skewness, such as the normal distribution, the mean, median, and mode are equal to each other, and 50% of points fall within each side of the central tendency measures.

If a distribution is right-skewed, its shape tails to the right, meaning the mean is greater than the median. Likewise, a left-skewed distribution has a mean less than its median.

Skewness can be calculated by 3 * (mean – mode) / standard deviation, which is the formula for Pearson’s skewness coefficient. Kurtosis measures the thickness of a distribution’s tails. A higher kurtosis indicates the presence of outliers, or more observations far from the center of the distribution. 

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