new;
output file=c:\jae\ols\norris\norris.out reset;
@Dataset Name:  Norris (norris11.dat)
Procedure:     Linear Least Squares Regression
Reference:     Norris, J., NIST.  
               Calibration of Ozone Monitors.
Data:          1 Response Variable (y)
               1 Predictor Variable (x)
               36 Observations
               Lower Level of Difficulty
               Observed Data

               y = B0 + B1*x + e
               Certified Regression Statistics

                                          Standard Deviation
     Parameter          Estimate             of Estimate
@
      cbcse={        -0.262323073774029     0.232818234301152,
                  1.00211681802045      0.429796848199937E-03};
cb=cbcse[.,1];
cstdb=cbcse[.,2];
     cR2= 0.999993745883712;

@Data:       y          x@

yx={
           0.1        0.2,
         338.8      337.4,
         118.1      118.2,
         888.0      884.6,
           9.2       10.1,
         228.1      226.5,
         668.5      666.3,
         998.5      996.3,
         449.1      448.6,
         778.9      777.0,
         559.2      558.2,
           0.3        0.4,
           0.1        0.6,
         778.1      775.5,
         668.8      666.9,
         339.3      338.0,
         448.9      447.5,
          10.8       11.6,
         557.7      556.0,
         228.3      228.1,
         998.0      995.8,
         888.8      887.6,
         119.6      120.2,
           0.3        0.3,
           0.6        0.3,
         557.6      556.8,
         339.3      339.1,
         888.0      887.2,
         998.5      999.0,
         778.9      779.0,
          10.2       11.1,
         117.6      118.3,
         228.9      229.2,
         668.4      669.1,
         449.2      448.9,
           0.2        0.5};
y=yx[.,1];x=yx[.,2];
@ane=ones(rows(y),1);@

ans1=nistols(y,x,cb,cstdb,cr2);  
ans2=niolsqr2(y,x,cb,cstdb,cr2);  
format /ld  6,1;
" Norris " ans1;  
"   (          "  ans2   "   ) ";
end;