推荐回答(4个)
设X是一个随机变量,若E{[X-E(X)]^2}存在,则称E{[X-E(X)]^2}为X的方差,记为D(X)或DX。即D(X)=E{[X-E(X)]^2},而σ(X)=D(X)^0.5(与X有相同的量纲)称为标准差或均方差。
由方差的定义可以得到以下常用计算公式:
D(X)=E(X^2)-[E(X)]^2
S^2=[(x1-x拔)^2+(x2-x拔)^2+(x3-x拔)^2+…+(xn-x拔)^2]/n
方差的几个重要性质(设一下各个方差均存在)。
(1)设c是常数,则D(c)=0。
(2)设X是随机变量,c是常数,则有D(cX)=(c^2)D(X)。
(3)设X,Y是两个相互独立的随机变量,则D(X+Y)=D(X)+D(Y)。
(4)D(X)=0的充分必要条件是X以概率为1取常数值c,即P{X=c}=1,其中E(X)=c。
方差是标准差的平方
方差:1/n[(x1-x)^2+(x2-x)^2+...+(xn-x)^2] n为个数 x为平均数 x1.2....n 为每个数
方差是在概率论和统计方差衡量随机变量或一组数据时离散程度的度量。概率论中方差用来度量随机变量和其数学期望(即均值)之间的偏离程度。统计中的方差(样本方差)是每个样本值与全体样本值的平均数之差的平方值的平均数。
极差是指一组测量值内最大值与 最小值之差,又称范围误差或 全距,以R表示。它是标志值变动的最大范围,它是测定标志变动的最简单的指标。
方差的意义:
当数据分布比较分散(即数据在平均数附近波动较大)时,各个数据与平均数的差的平方和较大,方差就较大;当数据分布比较集中时,各个数据与平均数的差的平方和较小。因此方差越大,数据的波动越大;方差越小,数据的波动就越小。
样本中各数据与样本平均数的差的平方和的平均数叫做样本方差;样本方差的 算术平方根叫做样本 标准差。样本方差和样本标准差都是衡量一个样本波动大小的量,样本方差或样本标准差越大,样本数据的波动就越大。
极差的用途与意义:
在统计中常用极差来刻画一组数据的离散程度,以及反映的是变量分布的变异范围和离散幅度,在总体中任何两个单位的标准值之差都不能超过极差。同时,它能体现一组数据波动的范围。极差越大,离散程度越大,反之,离散程度越小。
极差只指明了测定值的最大离散范围,而未能利用全部测量值的信息,不能细致地反映测量值彼此相符合的程度,极差是总体 标准偏差的有偏 估计值,当乘以校正系数之后,可以作为总体标准偏差的无偏估计值,它的优点是计算简单,含义直观,运用方便,故在 数据统计处理中仍有着相当广泛的应用。 但是,它仅仅取决于两个 极端值的水平,不能反映其间的变量分布情况,同时易受极端值的影响。
是一组测量值中最大值与最小值之差,以及表示,R=Xmax-Xmin。又称全距或范围误差。反映的是变量分布的变异范围和离散幅度,在总体中任何两个单位的标准值之差都不能超过极差。同时,它能体现一组数据波动的范围。
设X是一个随机变量,若E{[X-E(X)]^2}存在,则称E{[X-E(X)]^2}为X的方差,记为D(X)或DX。即D(X)=E{[X-E(X)]^2},而σ(X)=D(X)^0.5(与X有相同的量纲)称为标准差或均方差。
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