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Skewness

https://en.wikipedia.org/wiki/Skewness

https://www.investopedia.com/terms/s/skewness.asp

https://towardsdatascience.com/histograms-and-density-plots-in-python-f6bda88f5ac0

https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.skew.html

Skewness is a method for quantifying the lack of symmetry in the probability distribution of a variable.

• <spam style="background:#E6E6FA">Skewness = 0</spam> : Normally distributed.

• <spam style="background:#E6E6FA">Skewness < 0</spam> : Negative skew: The left tail is longer. The mass of the distribution is concentrated on the right of the figure. The distribution is said to be left-skewed, left-tailed, or skewed to the left, despite the fact that the curve itself appears to be skewed or leaning to the right; left instead refers to the left tail being drawn out and, often, the mean being skewed to the left of a typical center of the data. A left-skewed distribution usually appears as a right-leaning curve. https://en.wikipedia.org/wiki/Skewness

• <spam style="background:#E6E6FA">Skewness > 0 : Positive skew</spam> : The right tail is longer. the mass of the distribution is concentrated on the left of the figure. The distribution is said to be right-skewed, right-tailed, or skewed to the right, despite the fact that the curve itself appears to be skewed or leaning to the left; right instead refers to the right tail being drawn out and, often, the mean being skewed to the right of a typical center of the data. A right-skewed distribution usually appears as a left-leaning curve.

Taken from https://en.wikipedia.org/wiki/Skewness