In my 40 years as a professional statistician, I have yet to come across any person with a coefficient skewness and I am not sure that such a thing exists. That being the case, it has no usefulness.
Chat with our AI personalities
describe the properties of the standard deviation.
skewness=(mean-mode)/standard deviation
No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.No. Skewness is 0, but kurtosis is -3, not 3.
Karl Pearson simplified the topic of skewness and gave us some formulas to help. The first is the Pearson mode or first skewness coefficient. It is defined by the (mean-median)/standard deviation. So in this case the Pearson mode is: (8-6)/2 =1 There is also the Pearson Median. This is also called second skewness coefficient. It is defined as 3(mean-median)/standard deviation which in this case is 6/2 =3 hence the distribution is positive skewed
When the data are skewed to the right the measure of skewness will be positive.