Calculating Skewness and Kurtosis
Skewness is when a distribution is asymmetrical or lacks symmetry. The skewed portion is the long, thin part of the curve. Many researchers use skewed distribution to mean that the data are sparse at one of the distribution and piled up on the other end. An example is like the grades on a particular test that a teacher gives. The grade distribution is skewed, meaning that few students scored at one end of the grading scale, and many students scored at the other end. Like the relationship of A’s to C’s and B’s. It is more probable that you would have more C’s and B’s compared to A’s. So the tail of the skewed graph would be more of a bell towards the B’s and C’s. And the tapered off end would be the portion of the class that had gotten an A.The concept of skewness helps us to understand the relationship of the mean, median, and the mode. Now when graphing the skewness the mode is considered the high point or the apex. The mean tends to be located toward the tail of the distribution
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Some common words found in the essay are:
Bs Cs, , Cs Bs, mean median, coefficient skewness, normal tails, box whisker plot, lower upper quartiles, skewness kurtosis statistics, skewness mode, distribution mean, whisker plot, value distribution, upper quartiles, lower upper, box whisker,
Approximate Word count = 671
Approximate Pages = 3 (250 words per page double spaced)
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