Skewness

Okay, yes this blog had a lovely time down the shore. Now it's time to talk about skewness.

Wikipedia (5/24/2008), the free, on-line encyclopedia, defines skewness "in probability theory and statistics [as] a measure of the asymmetry of the probability distribution of a real-valued random variable." In English, this means, take a bunch of numbers, rank them from low to high, plot them as dots on a graph, and then connect the dots, you'll likely have a figure that bunches up high in the middle and tails off toward the right and the left. Ask yourself, "Which tail is longest?" Skeweness is a measure of how much longer the one tail is than the other. If the left tail is longer than the right, we say that the distribution is left-skewed, or negatively skewed. Credit card ownership can be said to be left (negatively) skewed because the average number of credit cards owned tends to be a pretty large number. If the right tail is longer than the left, we say that distribution is right (positively) skewed. Mother's age at the birth of her first child tends to be right (positively) skewed because most mothers tend to be in the teens or 20's when they first give birth. If the right and left tails are equal in length, skeweness is said to be equal to 0. The skewness of any normally distribution equals 0.

Skewness another powerful way of thinking about data. As such, the entrepreneur needs to know about it so he or she can think about his business and talk about his market to others. To learn more, read the entire Wikipedia article on it. And if something about this or anything else I've talked about resonates with you, post a comment.

Entrepreneurship informs everything I do. To read about entrepreneurial writing, go to www.kearneymusicschoolmurders.blogspot.com and for entrepreneurial real estate go to www.yourstopforrealestate.com/blog.