MATLAB数理统计程序.docVIP

正态总体均值、方差的参数估计与置信区间估计 P316 例6.5.1 置信区间估计 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 13.7097 muhat = 14.3318 sigmahat = 1.5595 muci = 13.4278 15.2358 sigmaci = 1.1374 2.5657 muhat = 14.7050 sigmahat = 1.8432 muci = 13.6365 15.7735 sigmaci = 1.3443 3.0324 P320例6.5.5 置信区间估计 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 = 4.7092 sigmahat = 0.2480 muci = 4.5516 4.8667 sigmaci = 0.1757 0.4211 P321 例6.5.6 置信区间估计 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 = 45.4000 sigmahat = 0.1803 muci = 45.2614 45.5386 sigmaci = 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 = 0 p = 0.0935 ci = 7.9747 8.3253 zval = 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（mumu0）； 若tail=0:表示单边假设检验（mumu0）； dim表示根据指定的维数进行检验 %[h,p,ci,zval]=ztest(X,mu,sigma,alpha) % X=normrnd(mu,sigma,N,M); 随机产生均值为mu，标准差为sigma的M行N例随机数； clear all; X=normrnd(100,5,100,1); mu=mean(X) sigmal=5; [h,p,ci,zval]=ztest(X,100,5,0.05) mu = 99.8810 h = 0 p = 0.8119 ci = 98.9011 100.8610 zval = -0.2379 单正态总体均值的假设检验 方差sigma未知时 P338 例7.2.2 %[h,p,ci,tstat]=ttest(X,mu0,alpha,tail,dim) clear all; X=[ 239.7 239.6 239 240 239.2]; [h,p,ci,tstat]=ttest(X,240,0.05) h = 1 p = 0.0491 ci = 239.0033 239.9967 tstat = tstat: