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{{Short description|Non-parametric statistical test between two distributions}}

{{Short description|Non-parametric statistical test between two distributions}}

[[文件:KS Example|缩略图|右|Kolmogorov–Smirnov统计数据的图示。 红线是累积分布函数，蓝线是经验分布函数，黑色箭头是K–S统计量。]]

[[文件:KS_Example.png|缩略图|右|Kolmogorov–Smirnov统计数据的图示。 红线是累积分布函数，蓝线是经验分布函数，黑色箭头是K–S统计量。]]

 

 

In [[statistics]], the '''Kolmogorov–Smirnov test''' ('''K–S test''' or '''KS test''') is a [[nonparametric statistics|nonparametric test]] of the equality of continuous (or discontinuous, see [[#Discrete and mixed null distribution|Section 2.2]]), one-dimensional [[probability distribution]]s that can be used to compare a [[random sample|sample]] with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).  It is named after  [[Andrey Kolmogorov]] and [[Nikolai Smirnov (mathematician)|Nikolai Smirnov]].

In [[statistics]], the '''Kolmogorov–Smirnov test''' ('''K–S test''' or '''KS test''') is a [[nonparametric statistics|nonparametric test]] of the equality of continuous (or discontinuous, see [[#Discrete and mixed null distribution|Section 2.2]]), one-dimensional [[probability distribution]]s that can be used to compare a [[random sample|sample]] with a reference probability distribution (one-sample K–S test), or to compare two samples (two-sample K–S test).  It is named after  [[Andrey Kolmogorov]] and [[Nikolai Smirnov (mathematician)|Nikolai Smirnov]].