Skewness is measured as the third standardised moment of the random variable.
Skewness is the expected value of {[X - E(X)]/sd(X)}3
where sd(X) = sqrt(Variance of X)
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if coefficient of skewness is zero then distribution is symmetric or zero skewed.
distinguish between dispersion and skewness
Negative skewness means the average (mean) will be less than the median. Positive skewness means the opposite. I'm not sure if any rule holds for the mode.
When we increase sample size the standard deviation( error) will be decrease and the nagetive skewness is converting to normality. shabirahmad666@rocketmail.com
Skewness is a measure of the extent to which the probability distribution of a random variable lies more to one side of the mean, as opposed to it being exactly symmetrical.If μ and s are the mean and standard deviation of a random variable X, thenSkew(X) = Expected value of [(X - μ)/s]3