17
Oct
Positive And Negative Skewness. If the data is positively skewed the coefficient is positive. It is the type of distribution where the data is more towards the lower side. If skewness is positive the data are positively skewed or skewed right meaning that the right tail of the distribution is longer than the left. If the curve shifts to the right it is considered positive skewness while a curve shifted to the left represents negative skewness.
If a return distribution shows a positive skew investors can expect recurrent small losses and few large returns from investment. And positive skew is when the long tail is on the positive side of the peak and some people say it is skewed to the right. However skewed data will increase the accuracy of the financial model. Some distributions with long tails include salaries people dont get negative salaries but the sky is the limit for CEOs and distances non-zero by definition but points. An example of positively skewed data is the life of bulbs. The skew is the direction that the curve is tilted in for degree of outcomes one chart showing more negative outcomes negative skew and one chart showing more positive outcomes positive skew.
Positive Skewness means when the tail on the right side of the distribution is longer or fatter.
By Rodolfo Hermans Godot at enwikipedia. Positive skewness has two applications in the field of asset management. Positive Skewness means when the tail on the right side of the distribution is longer or fatter. An example of positively skewed data is the life of bulbs. If the data is positively skewed the coefficient is positive. The probability distribution with its tail on the right side is a positively skewed distribution and the one with its tail on the left side is a negatively skewed distribution.