Skewness and Kurtosis - Part 5 - Examples on Pearsonian's Coefficient of Skewness - Statistics

A video explaining certain examples based on Pearsonian's Coefficient of Skewness.
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Skewness is a statistical measure that describes the asymmetry of a probability distribution of a real-valued random variable about its mean. A positive skewness indicates that the majority of values are concentrated on the left side of the mean, whereas a negative skewness indicates that the majority of values are on the right side of the mean. A distribution is considered symmetric if the skewness is close to 0. Skewness is important in statistics because it provides information about the shape of the distribution and can affect the mean, median, and standard deviation of a dataset.