A high kurtosis distribution has a sharper peak and longer, fatter tails, while a low kurtosis distribution has a more rounded peak and shorter thinner tails.
Distributions with zero excess kurtosis are called mesokurtic, or mesokurtotic. The most prominent example of a mesokurtic distribution is the normal distribution family, regardless of the values of its parameters. A few other well-known distributions can be mesokurtic, depending on parameter values: for example the binomial distribution is mesokurtic for .
A distribution with positive excess kurtosis is called leptokurtic, or leptokurtotic. In terms of shape, a leptokurtic distribution has a more acute peak around the mean (that is, a higher probability than a normally distributed variable of values near the mean) and fatter tails (that is, a higher probability than a normally distributed variable of extreme values). Examples of leptokurtic distributions include the Laplace distribution and the logistic distribution. Such distributions are sometimes termed super Gaussian.
The coin toss is the most platykurtic distributionA distribution with negative excess kurtosis is called platykurtic, or platykurtotic. In terms of shape, a platykurtic distribution has a lower, wider peak around the mean (that is, a lower probability than a normally distributed variable of values near the mean) and thinner tails (if viewed as the height of the probability density—that is, a lower probability than a normally distributed variable of extreme values). Examples of platykurtic distributions include the continuous or discrete uniform distributions, and the raised cosine distribution. The most platykurtic distribution of all is the Bernoulli distribution with p = ½ (for example the number of times one obtains "heads" when flipping a coin once, a coin toss), for which the kurtosis is −2. Such distributions are sometimes termed sub Gaussian.

楼上的英语真猛！

蜂度是衡量非正态的重要指标,这个指标在ICA很重要

偏度是指分布不对称的方向和程度，峰度是指分布图形的尖峭程度或峰凸程度。

这样的问题都问，看来统计学学的不是灰常好，只是知其然更要知其所以然，还是随便拿本统计学教材好好看一看吧