[Stata Program] /* Step 1 */ use http://www.gseis.ucla.edu/courses/data/cross1 corr api99 pctmeal pctel pctcred avged sw regress api99 pctmeal pctel pctcred avged, pe(.05) /* Step 2 */ use http://www.gseis.ucla.edu/courses/data/cross2 predict api99la1 generate api99la2 = 62.5067 + 130.5665*avged + 2.574684*pctcred - .6885639*pctmeal label variable api99la1 "OC api99 score using LA schools using predict" label variable api99la2 "OC api99 score using equation for LA schools" corr api99 api99la1 api99la2 corr api99 pctmeal pctel pctcred avged sw regress api99 pctmeal pctel pctcred avged, pe(.05) [Stata Output] /* Step 1 */ use http://www.gseis.ucla.edu/courses/data/cross1 corr api99 pctmeal pctel pctcred avged | api99 pctmeal pctel pctcred avged -------------+--------------------------------------------- api99 | 1.0000 pctmeal | -0.7559 1.0000 pctel | -0.7556 0.6551 1.0000 pctcred | 0.5909 -0.4211 -0.4041 1.0000 avged | 0.8863 -0.7410 -0.7833 0.4114 1.0000 sw regress api99 pctmeal pctel pctcred avged, pe(.05) begin with empty model p = 0.0000 < 0.0500 adding avged p = 0.0000 < 0.0500 adding pctcred p = 0.0003 < 0.0500 adding pctmeal Source | SS df MS Number of obs = 188 -------------+------------------------------ F( 3, 184) = 369.37 Model | 2347454.49 3 782484.831 Prob > F = 0.0000 Residual | 389795.423 184 2118.45338 R-squared = 0.8576 -------------+------------------------------ Adj R-squared = 0.8553 Total | 2737249.91 187 14637.7001 Root MSE = 46.027 ------------------------------------------------------------------------------ api99 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- avged | 130.5665 8.206563 15.91 0.000 114.3755 146.7576 pctcred | 2.574684 .3193867 8.06 0.000 1.944553 3.204815 pctmeal | -.6885639 .1870544 -3.68 0.000 -1.057611 -.3195166 _cons | 62.5067 37.88756 1.65 0.101 -12.2432 137.2566 ------------------------------------------------------------------------------ /* Step 2 */ use http://www.gseis.ucla.edu/courses/data/cross2 predict api99la1 generate api99la2 = 62.5067 + 130.5665*avged + 2.574684*pctcred - .6885639*pctmeal label variable api99la1 "OC api99 score using LA schools using predict" label variable api99la2 "OC api99 score using equation for LA schools" corr api99 api99la1 api99la2 (obs=52) | api99 api99la1 api99la2 -------------+--------------------------- api99 | 1.0000 api99la1 | 0.9312 1.0000 api99la2 | 0.9312 1.0000 1.0000 corr api99 pctmeal pctel pctcred avged (obs=52) | api99 pctmeal pctel pctcred avged -------------+--------------------------------------------- api99 | 1.0000 pctmeal | -0.9103 1.0000 pctel | -0.9293 0.9431 1.0000 pctcred | 0.5772 -0.5138 -0.4906 1.0000 avged | 0.9191 -0.9308 -0.9092 0.5342 1.0000 sw regress api99 pctmeal pctel pctcred avged, pe(.05) begin with empty model p = 0.0000 < 0.0500 adding pctel p = 0.0003 < 0.0500 adding avged p = 0.0310 < 0.0500 adding pctcred Source | SS df MS Number of obs = 52 -------------+------------------------------ F( 3, 48) = 152.62 Model | 690783.164 3 230261.055 Prob > F = 0.0000 Residual | 72420.2779 48 1508.75579 R-squared = 0.9051 -------------+------------------------------ Adj R-squared = 0.8992 Total | 763203.442 51 14964.7734 Root MSE = 38.843 ------------------------------------------------------------------------------ api99 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- pctel | -2.835101 .5641433 -5.03 0.000 -3.969387 -1.700815 avged | 59.32612 17.71861 3.35 0.002 23.70046 94.95178 pctcred | 2.645574 1.190507 2.22 0.031 .251899 5.039249 _cons | 336.6347 118.8344 2.83 0.007 97.7021 575.5672 ------------------------------------------------------------------------------