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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク chi distribution ： ウィキペディア英語版 chi distribution | cdf =$P(k/2,x^2/2)\backslash ,$| mean =$\backslash mu=\backslash sqrt\backslash ,\backslash frac$| median =| mode =$\backslash sqrt\backslash ,$ for $k\backslash ge\; 1$| variance =$\backslash sigma^2=k-\backslash mu^2\backslash ,$| skewness =$\backslash gamma\_1=\backslash frac\backslash ,(1-2\backslash sigma^2)$| kurtosis =$\backslash frac(1-\backslash mu\backslash sigma\backslash gamma\_1-\backslash sigma^2)$| entropy =$\backslash ln(\backslash Gamma(k/2))+\backslash ,$ $\backslash frac(k\backslash !-\backslash !\backslash ln(2)\backslash !-\backslash !(k\backslash !-\backslash !1)\backslash psi\_0(k/2))$| mgf =Complicated (see text)| char =Complicated (see text)| }} In probability theory and statistics, the chi distribution is a continuous probability distribution. It is the distribution of the square root of the sum of squares of independent random variables having a standard normal distribution. The most familiar examples are the Rayleigh distribution with chi distribution with 2 degrees of freedom, and the Maxwell distribution of (normalized) molecular speeds which is a chi distribution with 3 degrees of freedom (one for each spatial coordinate). If $X\_i$ are ''k'' independent, normally distributed random variables with means $\backslash mu\_i$ and standard deviations $\backslash sigma\_i$, then the statistic :$Y\; =\; \backslash sqrt\backslash right)^2\}$ is distributed according to the chi distribution. Accordingly, dividing by the mean of the chi distribution (scaled by the square root of ''n'' − 1) yields the correction factor in the unbiased estimation of the standard deviation of the normal distribution. The chi distribution has one parameter: $k$ which specifies the number of degrees of freedom (i.e. the number of $X\_i$). ==Characterization== 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「chi distribution」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.