样本X1,X2,X3来自总体X,若 hat (mu )=dfrac (1)(3)(X)_(1)+-|||-(X)_(2)+dfrac (1)(2)(X)_(3)
设sim N(mu ,1), X1、X2、X来自总体样本, hat (mu )=dfrac (2)(5)(X)_(1)+dfrac (2)(5)(X)_(2)+
4.设总体 sim N(mu ,(sigma )^2), x1,x2,x3为来自X的样本 hat (mu )=dfrac (1)(4)(x)_(1)+b(x)_
设X1,X2为来自正态总体N(μ,σ^2 )的样本,下列不是μ的无偏估计量的是-|||-A (mu )_(1)=dfrac (2)(3)(X)_(1)+dfra
x1,x2是取自总体N(μ,1)(μ未知)的样本。hat (mu )_(1)=dfrac (2)(3)(X)_(1)+dfrac (1)(3)(X)_(2) ;
10.设总体 sim N(mu ,(sigma )^2) ,X1,X2,X3是来自X的样本,则当 a= __ _时, mu =dfrac (1)(7)(X)_(
3.设x1,x2,x3是取自N(μ,1)的样本,以下μ的四个估计量中最有效的是 () .-|||-(A) (hat {mu )}_(1)=dfrac (1)(5
已知 X1,X2,X3 为来自总体 X 的样本, X1,X2,X3 X1,X2,X3 X1,X2,X3, 其中 X1,X2,X3的无偏估计量是 (
9.设x1,x2,x3是来自总体X的样本,若 (X)=u (未知), hat (mu )=dfrac (1)(2)(x)_(1)-a(x)_(2)+3a(x)_
21.设x1,x2,x3,x 4是来自均值为θ的指数分布总体的样本,其中θ未知,设有估计量-|||-_(1)=dfrac (1)(6)((x)_(1)+(x)_