use http://www.philender.com/courses/data/gpa, clear
sw regress gpa (greq grev) (mat ar), pr(.01) hier
begin with full model
p = 0.0113 >= 0.0100 removing mat ar
p = 0.0001 < 0.0100 keeping greq grev
Source | SS df MS Number of obs = 30
---------+------------------------------ F( 2, 27) = 12.73
Model | 5.06332584 2 2.53166292 Prob > F = 0.0001
Residual | 5.37134081 27 .198938548 R-squared = 0.4852
---------+------------------------------ Adj R-squared = 0.4471
Total | 10.4346666 29 .359816091 Root MSE = .44603
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gpa | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
greq | .0053559 .0019278 2.778 0.010 .0014003 .0093114
grev | .0027326 .0011288 2.421 0.022 .0004166 .0050487
_cons | -1.286698 .9765207 -1.318 0.199 -3.290353 .7169566
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sw regress gpa (greq grev) (mat ar), pe(.05) hier
begin with empty model
p = 0.0001 < 0.0500 adding greq grev
p = 0.0113 < 0.0500 adding mat ar
Source | SS df MS Number of obs = 30
---------+------------------------------ F( 4, 25) = 11.13
Model | 6.68313355 4 1.67078339 Prob > F = 0.0000
Residual | 3.7515331 25 .150061324 R-squared = 0.6405
---------+------------------------------ Adj R-squared = 0.5829
Total | 10.4346666 29 .359816091 Root MSE = .38738
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gpa | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------+--------------------------------------------------------------------
greq | .0039983 .0018307 2.184 0.039 .000228 .0077686
grev | .0015236 .0010502 1.451 0.159 -.0006392 .0036865
mat | .0208961 .0095488 2.188 0.038 .0012299 .0405623
ar | .1442335 .1130013 1.276 0.214 -.0884969 .376964
_cons | -1.738107 .9507399 -1.828 0.079 -3.696192 .2199789
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