Skewness, kurtosis

https://www.itl.nist.gov/div898/handbook/eda/section3/eda35b.htm

A fundamental task in many statistical analyses is to characterize the location and variability of a data set. A further characterization of the data includes skewness and kurtosis. Skewness is a measure of symmetry, or more precisely, the lack of symmetry. A distribution, or data set, is symmetric if it looks the same to the left and right of the center point.

Kurtosis is a measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution. That is, data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. A uniform distribution would be the extreme case.

The histogram is an effective graphical technique for showing both the skewness and kurtosis of data set.

skewness는 좌우 대칭인지를 보는 것이고, kurtosis는 normal dist.에 비해 fat tail인지 아닌지를 보는것. high kurtosis라고 하면 heavy tail을 가지고 있다는 뜻.