在统计学中，峰度（Kurtosis）衡量实数随机变量概率分布的峰态。峰度高就意味着方差增大是由低频度的大于或小于平均值的极端差值引起的。

四阶标准矩可以定义为：

其中μ₄是四阶中心矩，σ是标准差。

在更通常的情况下，峰度被定义为四阶累积量除以二阶累积量的平方，它等于四阶中心矩除以概率分布方差的平方再减去3：

这也被称为超值峰度（excess kurtosis）。「减3」是为了让正态分布的峰度为0。

假定Y为n个独立变量之和，且这些变量和X具有相同的分布，那么：Kurt[Y] = Kurt[X] / n， 但如果峰度被定义为：μ₄ / σ，公式可变得更加复杂。

In probability theory and statistics, kurtosis (from Greek:κυρτός, kyrtos or kurtos, meaning "curved, arching") is a measure of the "tailedness" of the probability distribution of a real-valued random variable. In a similar way to the concept of skewness, kurtosis is a descriptor of the shape of a probability distribution and, just as for skewness, there are different ways of quantifying it for a theoretical distribution and corresponding ways of estimating it from a sample from a population. Depending on the particular measure of kurtosis that is used, there are various interpretations of kurtosis, and of how particular measures should be interpreted.