How does skewness and kurtosis affect your distribution?
Use skewness and kurtosis to help you establish an initial understanding of your data. Skewness is the extent to which the data are not symmetrical. Whether the skewness value is 0, positive, or negative reveals information about the shape of the data. As data becomes more symmetrical, its skewness value approaches zero.
What does a kurtosis value of 0 mean?
Normally distributed data establishes the baseline for kurtosis. Sample kurtosis that significantly deviates from 0 may indicate that the data are not normally distributed. A distribution with a positive kurtosis value indicates that the distribution has heavier tails and a sharper peak than the normal distribution.
How is left skewed data related to failure rate?
Left skewed or negative skewed data is so named because the “tail” of the distribution points to the left, and because it produces a negative skewness value. Failure rate data is often left skewed. Consider light bulbs: very few will burn out right away, the vast majority lasting for quite a long time.
What is the skewness of a right skewed distribution?
Positive or right skewed distributions. Positive skewed or right skewed data is so named because the “tail” of the distribution points to the right, and because its skewness value will be greater than 0 (or positive).
How does outliers affect the kurtosis of a distribution?
Kurtosis. As skewness involves the third moment of the distribution, kurtosis involves the fourth moment. The outliers in a sample, therefore, have even more effect on the kurtosis than they do on the skewness and in a symmetric distribution both tails increase the kurtosis, unlike skewness where they offset each other.
How does skewness affect the shape of data?
Skewness is the extent to which the data are not symmetrical. Whether the skewness value is 0, positive, or negative reveals information about the shape of the data. As data becomes more symmetrical, its skewness value approaches zero.