sas程序整理

6.2求置信区间程序
data ex;
input x@@;
cards;
24.3 20.8 23.7 19.3 17.4
;
proc capability; intervals x/method=4,6
alpha=0.05type=twosided;
run;
7.1
一个正态总体均值的假设检验
data ex;
input x@@;
y=x-14;
cards;
10.4 12 13.2 13.7 14.6 15.1 15.5 15.9
;
proc means mean std t prt ;var y;
run;
两个正态总体均值作假设检验的sas程序data ee; do a=1to2;do i=1to8;
input x@@;output ;end;end;
cards;
8.6 8.7 5.6 9.3 8.4 9.3 7.5 7.9
8 7.9 5.8 9.1 7.7 8.2 7.4 6.6
;
proc ttest; class a;
var x;run;
7.2
总体分布做x^2检验程序
data ex;
input n np@@;
k+(n-np)**2/np;
c=cinv(0.95,6);
cards;
67.81613.231718.522619.44
1116.33911.439 6.866 6.26
;
proc print; var k c;
run;
总体分布的正态性检验：
data ex ;
input x@@;
cards;
10.4 12 13.1 13.8 14.6 15.1 15.5 15.9
;
proc univariate normal;run;
列链表分类标识的独立性检验sas程序Chi-Square（卡方）data ex;
do a=1to3;do b=1to3;
input f@@;output ;end;end;
cards;
32 38 58 45 44 28 14 18 23
;
proc freq;weight f;
tables a*b/chisq;run;
8.1 单因素实验方差分析
（1）不等重复情形
data ex;
do a=1to3;input n@@;
do i= 1to n;input x@@;
output; end;end;
cards;
8 21 29 24 22 25 30 27 26
10 20 25 25 23 29 31 24 26 20 21
6 24 22 28 25 21 26
;
proc anova;class a; model x=a;
means a/lsd duncan cldiff ;run;
（2）等重复情形
data ex;
do a=1to4;do i=1to4;
input x@@;
output ;end;end;
cards;
19 23 21 13 21 24 27 20
20 18 19 15 22 25 27 22
proc anova;class a; model x=a; means a/lsd duncan cldiff ;run;
8.2
双因素实验方差分析（一）
data ex ;do a=1to4;do b=1to5; input x @@;
output;end;end;
cards;
53 56 45 52 49 47 50 47 47 53
57 63 54 57 58 45 52 42 41 48
;
proc anova; class a b;
model x=a b ;
means a b/lsd duncan cldiff ;run; 双因素实验方差分析（二）
data ex ;do a=1to4;do b=1to3; do i=1to2;input x @@;
output;end;end;end;
cards;
58.2 52.6 56.2 41.2 65.3 60.8
49.1 42.8 54.1 50.5 51.6 48.4
60.1 58.3 70.9 73.2 39.2 40.7
75.8 71.5 58.2 51.0 48.7 41.4
;
proc anova; class a b;
model x=a b a*b;
means a b/lsd duncan cldiff ;run;
9.1 线性回归的sas
data ex ;input x y @@;
cards;
1.5 4.8 1.8 5.7
2.4 7 3 8.3
3.5 10.9 3.9 12.4
4.4 13.1
4.8 13.6 5 1
5.3 2 .
;
proc gplot;
plot y*x;
symbol i=rl v =dot ;
proc reg;
model y=x/cli ;
run;
9.2 非线性回归的sas
（1）线性化后线性回归
data ex;
input x y@@;
x1 = 1/x; lx=log(x);ly=log(y);
cards;
1 1.85
2 1.37
3 1.02
4 0.7
5 4 0.56
6 0.41 6 0.31 8 0.23 8 0.17
;
proc reg ;model y=x1;
proc reg ;model ly=lx;
proc reg; model ly=x;run;
(2)非线性回归方程的剩余平方和
Data ex;
x1=1/x;lx=log(x);ly=log(y);
y1=0.1159+1.9291*x1;q1+(y-y1)**2;
y2=exp(0.9638-1.1292*lx);q2+(y-y2)**2;
y3=exp(0.9230-0.3221*x);q3+(y-y3)**2;
cards;
1 1.85
2 1.37
3 1.02
4 0.7
5 4 0.56
6 0.41 6 0.31 8 0.23 8 0.17
;
proc print;var q1-q3;run;
9.3 协方差分析的sas
（1）单因素实验
data ex;
do a=1to3;do i=1to8;
input x y@@;output ;end;end;
cards;
47 54 58 66 53 63 46 51 49 56 56 66 54 61 44 50 52 54 53 53 64 67 58 62 59 62 61 63 63 64 66 69 44 52 48 58 46 54 50 61 59 70 57 64 58 69 53 66 ;
proc glm;class a;model y=x a/solution;
lsmeans a/stderr pdiff;run;
(2)双因素不考虑交互作用情景
data ex;
do a=1to3;do b=1to5;
input x y@@;
output;end;end;
cards;
8 2.85 10 4.24 12 3 11 4.94 10 2.88
10 3.14 12 4.5 7 2.75 12 5.84 10 4.06
12 3.88 10 3.86 9 2.82 10 4.94 9 2.89
;
proc glm;class a b;model y=x a b/solution; lsmeans a b/stderr pdiff;run;
（3）双因素分析考虑交互情景
data ex; do a=1to4;do b=1to2;
do i=1to2;input x y @@;
output;end;end;end;
cards;
14.6 97.8 12.1 94.2 19.5 113.2 18.8 110.1
13.6 100.3 12.9 98.5 18.5 119.4 18.2 114.7
12.8 99.2 10.7 89.6 18.2 122.2 16.9 105.3
12 102.1 12.4 103.8 16.4 117.2 17.2 117.9
;
proc glm; class a b;model y=x a b a*b/solution; lsmeans a b/stderr pdiff;run;。