Section01_契比雪夫不等式

P{∣X−EX∣≥ϵ}≤DXϵ2P{∣X−EX∣<ϵ}≥1−DXϵ2 \begin{split} \mathbb{P}\{\vert X-EX \vert \ge \epsilon\} \le \frac{DX}{\epsilon^{2}} \\ \mathbb{P}\{\vert X-EX \vert < \epsilon\} \ge 1 - \frac{DX}{\epsilon^{2}} \end{split}

  • 例 设随机变量 X1,X2,⋯ ,XnX_{1},X_{2},\cdots,X_{n} 独立同分布,且 X1X_{1} 的四阶矩存在,记 uk=E(X1k),k=1,2,3,4u_{k} = E(X_{1}^{k}), \quad k = 1,2,3,4,由契比雪夫不等式,对 ∀ ϵ>0\forall\ \epsilon>0,有 P{∣1n∑i=1nXi2−u2∣≥ϵ}≤\mathbb{P}\{\vert \frac{1}{n}\sum\limits_{i=1}^{n}X_{i}^{2} - u_{2} \vert \ge \epsilon\} \le ( ) ∵X1,X2,⋯ ,Xn独立同分布∴E(1n∑i=1nXi2)=1n∑i=1∞EXi2=1n×n×EX12=u2D(1n∑i=1nXi2)=1n2∑i=1nDXi2=1n2×nDX12=EX14−(EX2)2n=u4−u22n∵P{∣X−EX∣≥ϵ}≤DXϵ2∴P{∣1n∑i=1nXi2−u2∣≥ϵ}≤u4−u22nϵ2 \begin{array}{ll} \because & X_{1},X_{2},\cdots,X_{n}\text{独立同分布} \\ \therefore & E(\frac{1}{n}\sum\limits_{i=1}^{n} X^{2}_{i}) = \frac{1}{n}\sum\limits_{i=1}^{\infty}EX_{i}^{2} = \frac{1}{n}\times n\times EX_{1}^{2} = u_{2}\\ & D(\frac{1}{n}\sum\limits_{i=1}^{n} X^{2}_{i}) = \frac{1}{n^{2}}\sum\limits_{i=1}^{n}DX^{2}_{i} = \frac{1}{n^{2}}\times n DX^{2}_{1} = \frac{EX_{1}^{4} - (EX^{2})^{2}}{n} \\ & =\frac{u_{4} - u_{2}^{2}}{n} \\ \because & \mathbb{P}\{\vert X - EX \vert\ge \epsilon\} \le \frac{DX}{\epsilon^{2}} \\ \therefore & \mathbb{P}\{\vert \frac{1}{n}\sum\limits_{i=1}^{n}X_{i}^{2} - u_{2} \vert \ge \epsilon\} \le \frac{u_{4} - u_{2}^{2}}{n\epsilon^{2}} \\ \end{array}

results matching ""

    No results matching ""