/* one-sample t-test */
data gr;
input r @@; /* @@ tells SAS to look for multiple observations per line */
datalines;
1.66 1.61 1.62 1.69 1.58 1.43 1.66
1.69 1.58 1.20 1.52 1.60 1.55 1.67
1.77 1.50 1.64 1.54 1.40 1.36 1.50
1.40 1.35 1.48 1.64 1.91 1.70
;
run;

proc print data = gr;
run;

proc ttest data = gr h0=1.618;
var r;
run;


/* two-sample t-test */

data wt;
input resp diet $ @@;
datalines;
93 LFD 172 LFD 617 LFD 534 LFD
500.5 LFD 127 LFD 1224 LFD 143 LFD
852 LFD 134 LFD 547.5 LFD 595.5 HFD
418.5 HFD 642 HFD 743.5 HFD 1351 HFD
1180 HFD 938.5 HFD 670 HFD 1319 HFD
1007 HFD 589 HFD 481.5 HFD 785 HFD
1060 HFD 435 HFD 535.5 HFD
;
run;

proc print data = wt;
run;

proc ttest data = wt;
class diet;
var resp;
run;


/* One-way ANOVA: Testing equality of more than 2 means */

data slopest;
input trt $ slope @@;
datalines;
X 1.23 Y 1.80 X 1.81 X 1.29
Y 2.89 X 1.58 Y 0.99 C 1.24
Y 1.26 C 1.57 C 1.27 C 1.19
Y 1.82 C 1.76 X 1.91 Y 1.25
X 1.09 X 1.29 Y 1.12 C 1.51
Y 2.13 X 1.16 Y 0.62 C 1.04
;
run;

proc print data = slopest;
run;


proc anova data = slopest;
class trt;
model slope = trt;
means trt / tukey cldiff;
run;


/* simple linear regression */

data rbc;
input hem rbc @@;
datalines;
14.8 5.27 15.7 5.26 11.4 3.98
13.6 4.64 12.6 4.44 12.5 4.96
12.7 4.77 12.0 4.89 13.4 4.61
12.9 4.78 13.2 4.75 11.7 4.14
13.7 5.06 12.5 4.33 12.2 4.10
13.6 4.24 14.1 5.19 14.2 4.93
13.6 4.96 14.0 4.94 15.8 5.31
13.1 4.43 12.4 4.45 13.5 4.79
14.3 4.69
;
run;

proc reg data = rbc;
model rbc = hem;
run;



/* chi-squared test of association */

data ae;
input trt $ abdpain $ count;
datalines;
placebo yes 2
placebo no 1376
vaccine yes 29
vaccine no 4965
;
run;


proc freq data = ae;
tables trt*abdpain / chisq;
weight count;
run;