Chebyshev's inequality 切比雪夫不等式

In probability theory, Chebyshev’s inequality (also spelled as Tchebysheff’s inequality) guarantees that in any data sample or probability distribution,  “nearly all” values are close to the mean — the precise statement being that no more than 1/k2 of the distribution’s values can be more than k standard deviations away from the mean. The inequality has great utility because it can be applied to completely arbitrary distributions (unknown except for mean and variance), for example it can be used to prove the weak law of large numbers.

http://en.wikipedia.org/wiki/Chebyshev's_inequality

在機率論中，切比雪夫不等式（Chebyshev's Inequality）顯示了隨機變數的「幾乎所有」值都會「接近」平均。切比雪夫不等式，對任何分布形狀的數據都適用。

http://zh.wikipedia.org/zh-tw/%E5%88%87%E6%AF%94%E9%9B%AA%E5%A4%AB%E4%B8%8D%E7%AD%89%E5%BC%8F