SAS中区间估计与假设检验 很全很好课件

Sas中能进行区间估计和假设检验的过程及语句很多，我们主要介绍：Means（summary）过程Univariate

过程Capability过程Ttest过程区间估计与假设检验Procmeansdata=classclm

maxdec=2alph=0.01;Varheight;Run;Procmeansdata=classmeanvar

clmalpha=0.01maxdec=3fw=8;Varheightweight;Outputout=mclassmean=var=vh

vw

lclm=lc

uclm=uc;Run;注：means过程只能对均值进行区间估计大前提是该变量服从正态分布Means过程做区间估计Procunivariatedata=classcibasic(alph=0.01);Varheight;Run;注：可以对均值、标准差及方差进行区间估计大前提是该变量服从正态分布Univariate过程做区间估计Dataclass0;Setclass;H0=height-62.33;Procmeansdata=class0tprobt

/*prt*/;VarH0;Run;注：means过程只能对均值=0进行假设检验，大前提是该变量服从正态分布Means过程做假设检验Procunivariatedata=class;Varheight;Run;注：缺省情况下对均值=0进行假设检验大前提是该变量服从正态分布Univariate过程做假设检验Proc

univariatedata=classmu0=62;Varheight;Outputout=t_testt=t_valueprobt=p_value;Run;ProcCapabilitydata=class;Varheight;Run;注：缺省情况下对均值=0进行假设检验大前提是该变量服从正态分布Capability过程做假设检验Proc

Capabilitydata=classmu0=62;Varheight;Run;PROCTTEST格式PROCTTEST<选项>;CLASS变量；PAIRED变量串；BY变量串；VAR变量串；FREQ变量串；WEIGHT变量；RUN;ttest配对的t检验

简便法(x)常规法(y)2.41002.80002.90003.04002.75001.88002.23003.43003.67003.81004.49004.00005.16004.44005.45005.41002.06001.24001.64001.83001.06001.45000.77000.9200现有两种方法测定血液中的某种物质的含量，简便法和常规法，对12个人同时用两种方法进行测定，分析两种方法是否显著不同？Procttestdata=ah0=0alpha=0.05/*缺省选项*/;pairedx*y;Run;Paired语句设置举例Paireda*b;Paireda*bc*d;Paired(ab)*(cd);Paired(ab)*(cb);Paired(a1-a2)*(b1-b2);Paired(a1-a2):(b1-b2);a-ba-b,c-da-c,a-d,b-c,b-da-c,a-b,b-ca1-b1,a1-b2,a2-b1,a2-b2a1-b1,a2-b2左栏中的“-”是破折号表示“到”，“至”的意思，右栏中的“-”是减号正态性检验前面的区间估计和假设检验都要假设变量为正态，所以在进行区间估计或检验之前一定要进行正态性检验Procunivariatedata=classnormal;Varheight;Run;自编程序进行区间估计和假设检验当要进行的估计或检验没有现成的过程或语句可用时，可以自编程序进行估计或检验。下表给出一公司生产的60个抽样轴承滚珠直径（单位：厘米）试求轴承滚珠直径方差的98%的置信区间1.7381.7291.7431.7401.7361.7411.7351.7311.7261.7371.7281.7371.7361.7351.7241.7331.7421.7361.7391.7351.7451.7361.7421.7401.7281.7381.7251.7331.7341.7321.7331.7301.7321.7301.7391.7341.7381.7391.7271.7351.7351.7321.7351.7271.7341.7321.7361.7411.7361.7441.7321.7371.7311.7461.7351.7351.7291.7341.7301.740示例datazhoucheng;inputx@@;cards;1.7381.7291.7431.7401.7361.7411.7351.7311.7261.7371.7281.7371.7361.7351.7241.7331.7421.7361.7391.7351.7451.7361.7421.7401.7281.7381.7251.7331.7341.7321.7331.7301.7321.7301.7391.7341.7381.7391.7271.7351.7351.7321.7351.7271.7341.7321.7361.7411.7361.7441.7321.7371.7311.7461.7351.7351.7291.7341.7301.740;Proc

univariatedata=zhouchengnormal;Varx;outputout=bmean=mstd=s;run;示例续datac;setb;k1=cinv(0.01,59);k2=cinv(0.99,59);a1=59*s**2/k2;a2=59*s**2/k1;keepk1k2a1a2;run;总体均值已知时，如何自编这个程序？两组均数差别比较的U（Z）检验将20名贫血患儿随机分成两组，分别用新药和常规药进行