Question

Who the following did not develop the measurement of skewness?
(A) Croxton
(B) Karl Pearson
(C) Kalley
(D) Bowley

Answer 1

Answer:

(B) Karl Pearson

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Answer 2

Answer:

In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean. The skewness value can be positive, zero,negative or undefined

For a unimodal distribution, negative skew commonly indicates that the tail is on the left side of the distribution, and positive skew indicates that the tail is on the right. In cases where one tail is long but the other tail is fat, skewness does not obey a simple rule. For example, a zero value means that the tails on both sides of the mean balance out overall; this is the case for a symmetric distribution, but can also be true for an asymmetric distribution where one tail is long and thin, and the other is short but fat.

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