Not to be flippant, but why do you care? I cannot recall an instance in which knowing the value of a formal measure of skewness (let alone kurtosis) was useful. Observing that a distribution is skewed is useful; the formal skewness coefficient is not, so far as I have had occasion to observe.
it "may" (emphasis on may) be helpful on occasion ... to compare two distributions in terms of skewness and the eye might not be so sure ... perhaps a quantitative value would be of "some" value
however, at least for introductory work ... if the eye can't see it ... then the difference is probably not important
For students in an introductory course (which I take to be what you're engaged in, but I might be wrong about that -- you haven't actually said), I would not bother much with skewness and kurtosis, except to point out that the concepts exist, and measures of both are sometimes used but not very frequently, and supply a citation or two for those who really want to calculate values as a recreational activity.
i think that it can be helpful to know that IF a distribution is highly skewed (large n and rather smooth) ... that the mean and median won't be the same ... take in a large n distribution of salaries ... the mean salary will usually be further UP the scale than will be the median ... this could be important IF one were trying to make the case that either salaries were good ... or bad ...
which measure of average is reported could help or hurt one's case
. . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
