方差的参数估计和置信区间估计

正态总体均值、方差的参数估量与置信区间估量P316 例 6.5.1 置信区间估量clear;Y=[14.85 13.01 13.50 14.93 16.97 13.80 17.95 13.37 16.29 12.38];X=normrnd(15,2,10,1) % 随机产生数[muhat,sigmahat,muci,sigmaci]=normfit(X,0.1) % 正态拟合[muhat,sigmahat,muci,sigmaci]=normfit(Y,0.1) % 正态拟合X = 15.2573 16.3129 12.6644 14.0788 14.4751 12.5737 12.3611 16.8624 15.0225 13.7097muhat = 14.3318sigmahat = 1.5595muci = 13.4278 15.2358sigmaci = 1.1374 2.5657muhat = 14.7050sigmahat = 1.8432muci = 13.6365 15.7735sigmaci = 1.3443 3.0324P320 例 6.5.5 置信区间估量clear;Y=[4.68 4.85 4.32 4.85 4.61 5.02 5.20 4.60 4.58 4.72 4.38 4.70];[muhat,sigmahat,muci,sigmaci]=normfit(Y,0.05)muhat = 4.7092sigmahat = 0.2480muci = 4.5516 4.8667sigmaci = 0.1757 0.4211 P321 例 6.5.6 置信区间估量clear;Y=[45.3 45.4 45.1 45.3 45.5 45.7 45.4 45.3 45.6];[muhat,sigmahat,muci,sigmaci]=normfit(Y,0.05)muhat = 45.4000sigmahat = 0.1803muci = 45.2614 45.5386sigmaci = 0.1218 0.3454 单正态总体均值的假设检验 方差 sigma 已知时P338 例 7.2.1 %[h,p,ci,zval]=ztest(X,mu,sigma,alpha,tail,dim)clear all;X=[ 8.05 8.15 8.2 8.1 8.25];[h,p,ci,zval]=ztest(X,8,0.2,0.05)h = 0p = 0.0935ci = 7.9747 8.3253zval = 1.6771注：p 为观察值的概率ci 为置信区间；zval 统计量值若 h=0: 表示在显著性水平 alpha 下，不能否定原假设；若 h=1: 表示在显著性水平 alpha 下，否定原假设；若 tail=0:表示双边假设检验；若 tail=1:表示单边假设检验（mu>mu0）；若 tail=0:表示单边假设检验（mu