Chernoff's inequality

From Wikipedia, the free encyclopedia

In probability theory, Chernoff's inequality, named after Herman Chernoff, states the following. Let

X_1,X_2,\dots,X_n

be independent random variables, such that

E[X_i]=0 \,

and

\left|X_i\right|\leq 1\, for all i.

Let

X=\sum_{i=1}^n X_i

and let σ2 be the variance of X. Then

P(\left|X\right|\geq k\sigma)\leq 2e^{-k^2/4}

for any

0 \leq k \leq 2 \sigma.\,

[edit] See also

Languages