--------------------------------------------------------------------------------- name: log: C:\Users\LabProf01\Documents\Reset.log log type: text opened on: 27 Sep 2022, 16:53:00 . reg price lotsize sqrft bdrms Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(3, 84) = 57.46 Model | 617130.701 3 205710.234 Prob > F = 0.0000 Residual | 300723.805 84 3580.0453 R-squared = 0.6724 -------------+---------------------------------- Adj R-squared = 0.6607 Total | 917854.506 87 10550.0518 Root MSE = 59.833 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | .0020677 .0006421 3.22 0.002 .0007908 .0033446 sqrft | .1227782 .0132374 9.28 0.000 .0964541 .1491022 bdrms | 13.85252 9.010145 1.54 0.128 -4.065141 31.77018 _cons | -21.77031 29.47504 -0.74 0.462 -80.38466 36.84405 ------------------------------------------------------------------------------ . predict yhat variable yhat already defined r(110); . clear all . use "C:\Users\LabProf01\Downloads\hprice1.dta" . reg price lotsize sqrft bdrms Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(3, 84) = 57.46 Model | 617130.701 3 205710.234 Prob > F = 0.0000 Residual | 300723.805 84 3580.0453 R-squared = 0.6724 -------------+---------------------------------- Adj R-squared = 0.6607 Total | 917854.506 87 10550.0518 Root MSE = 59.833 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | .0020677 .0006421 3.22 0.002 .0007908 .0033446 sqrft | .1227782 .0132374 9.28 0.000 .0964541 .1491022 bdrms | 13.85252 9.010145 1.54 0.128 -4.065141 31.77018 _cons | -21.77031 29.47504 -0.74 0.462 -80.38466 36.84405 ------------------------------------------------------------------------------ . predict yhat (option xb assumed; fitted values) . gen yhat2=yhat^2 . gen yhat3=yhat^3 . reg price lotsize sqrft bdrms yhat2 yhat3 Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(5, 82) = 39.35 Model | 647870.679 5 129574.136 Prob > F = 0.0000 Residual | 269983.827 82 3292.48569 R-squared = 0.7059 -------------+---------------------------------- Adj R-squared = 0.6879 Total | 917854.506 87 10550.0518 Root MSE = 57.38 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | .0001538 .005203 0.03 0.976 -.0101967 .0105043 sqrft | .017602 .2992508 0.06 0.953 -.5777031 .6129071 bdrms | 2.175252 33.8881 0.06 0.949 -65.23897 69.58948 yhat2 | .0003534 .0070989 0.05 0.960 -.0137687 .0144754 yhat3 | 1.55e-06 6.55e-06 0.24 0.814 -.0000115 .0000146 _cons | 166.0939 317.4324 0.52 0.602 -465.3803 797.5682 ------------------------------------------------------------------------------ . test yhat2 yhat3 ( 1) yhat2 = 0 ( 2) yhat3 = 0 F( 2, 82) = 4.67 Prob > F = 0.0120 . reg price lotsize sqrft bdrms yhat2 Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(4, 83) = 49.75 Model | 647687.58 4 161921.895 Prob > F = 0.0000 Residual | 270166.926 83 3255.0232 R-squared = 0.7057 -------------+---------------------------------- Adj R-squared = 0.6915 Total | 917854.506 87 10550.0518 Root MSE = 57.053 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | -.0010406 .0011849 -0.88 0.382 -.0033974 .0013162 sqrft | -.0515996 .0582962 -0.89 0.379 -.1675484 .0643491 bdrms | -5.406923 10.64541 -0.51 0.613 -26.58021 15.76636 yhat2 | .0020201 .0006593 3.06 0.003 .0007087 .0033315 _cons | 237.8931 89.28748 2.66 0.009 60.30388 415.4823 ------------------------------------------------------------------------------ . twoway (scatter price yhat, sort) . reg lprice llotsize lsqrft bdrms Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(3, 84) = 50.42 Model | 5.15504028 3 1.71834676 Prob > F = 0.0000 Residual | 2.86256324 84 .034078134 R-squared = 0.6430 -------------+---------------------------------- Adj R-squared = 0.6302 Total | 8.01760352 87 .092156362 Root MSE = .1846 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- llotsize | .1679667 .0382812 4.39 0.000 .0918404 .244093 lsqrft | .7002324 .0928652 7.54 0.000 .5155597 .8849051 bdrms | .0369584 .0275313 1.34 0.183 -.0177906 .0917074 _cons | -1.297042 .6512836 -1.99 0.050 -2.592191 -.001893 ------------------------------------------------------------------------------ . predict lyhat (option xb assumed; fitted values) . gen lyhat2= lyhat^2 . gen lyhat3= lyhat^3 . reg lprice llotsize lsqrft bdrms lyhat2 lyhat3 Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(5, 82) = 32.41 Model | 5.32360036 5 1.06472007 Prob > F = 0.0000 Residual | 2.69400316 82 .032853697 R-squared = 0.6640 -------------+---------------------------------- Adj R-squared = 0.6435 Total | 8.01760352 87 .092156362 Root MSE = .18126 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- llotsize | -4.190767 12.59521 -0.33 0.740 -29.24665 20.86512 lsqrft | -17.38995 52.48991 -0.33 0.741 -121.8091 87.0292 bdrms | -.927485 2.769755 -0.33 0.739 -6.437411 4.582441 lyhat2 | 3.920341 13.01424 0.30 0.764 -21.96914 29.80982 lyhat3 | -.1933459 .7520741 -0.26 0.798 -1.689461 1.302769 _cons | 88.07241 240.9744 0.37 0.716 -391.3024 567.4472 ------------------------------------------------------------------------------ . test lyhat2 lyhat3 ( 1) lyhat2 = 0 ( 2) lyhat3 = 0 F( 2, 82) = 2.57 Prob > F = 0.0831 . reg lprice lotsize sqrft bdrms lyhat Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(4, 83) = 37.82 Model | 5.17697636 4 1.29424409 Prob > F = 0.0000 Residual | 2.84062716 83 .034224424 R-squared = 0.6457 -------------+---------------------------------- Adj R-squared = 0.6286 Total | 8.01760352 87 .092156362 Root MSE = .185 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | 9.40e-08 3.08e-06 0.03 0.976 -6.03e-06 6.21e-06 sqrft | .0000769 .0001293 0.59 0.554 -.0001803 .000334 bdrms | .0006235 .0297743 0.02 0.983 -.0585963 .0598433 lyhat | .8277844 .3533739 2.34 0.022 .1249379 1.530631 _cons | .8122861 1.687441 0.48 0.632 -2.543966 4.168538 ------------------------------------------------------------------------------ . reg lprice lotsize sqrft bdrms Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(3, 84) = 46.13 Model | 4.98917377 3 1.66305792 Prob > F = 0.0000 Residual | 3.02842975 84 .036052735 R-squared = 0.6223 -------------+---------------------------------- Adj R-squared = 0.6088 Total | 8.01760352 87 .092156362 Root MSE = .18988 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lotsize | 5.60e-06 2.04e-06 2.75 0.007 1.55e-06 9.65e-06 sqrft | .0003641 .000042 8.67 0.000 .0002806 .0004477 bdrms | .0252388 .0285928 0.88 0.380 -.0316211 .0820987 _cons | 4.759375 .0935361 50.88 0.000 4.573369 4.945382 ------------------------------------------------------------------------------ . predict lpricehat (option xb assumed; fitted values) . reg lprice llotsize lsqrft bdrms lpricehat Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(4, 83) = 37.78 Model | 5.17529499 4 1.29382375 Prob > F = 0.0000 Residual | 2.84230853 83 .034244681 R-squared = 0.6455 -------------+---------------------------------- Adj R-squared = 0.6284 Total | 8.01760352 87 .092156362 Root MSE = .18505 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- llotsize | .1343729 .0581433 2.31 0.023 .0187283 .2500175 lsqrft | .4502068 .3381665 1.33 0.187 -.2223928 1.122806 bdrms | .0250604 .0316389 0.79 0.431 -.037868 .0879888 lpricehat | .3320074 .4316993 0.77 0.444 -.5266251 1.19064 _cons | -.9323427 .8069176 -1.16 0.251 -2.537269 .6725839 ------------------------------------------------------------------------------ . reg lprice llotsize lsqrft bdrms Source | SS df MS Number of obs = 88 -------------+---------------------------------- F(3, 84) = 50.42 Model | 5.15504028 3 1.71834676 Prob > F = 0.0000 Residual | 2.86256324 84 .034078134 R-squared = 0.6430 -------------+---------------------------------- Adj R-squared = 0.6302 Total | 8.01760352 87 .092156362 Root MSE = .1846 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- llotsize | .1679667 .0382812 4.39 0.000 .0918404 .244093 lsqrft | .7002324 .0928652 7.54 0.000 .5155597 .8849051 bdrms | .0369584 .0275313 1.34 0.183 -.0177906 .0917074 _cons | -1.297042 .6512836 -1.99 0.050 -2.592191 -.001893 ------------------------------------------------------------------------------ . log close name: log: C:\Users\LabProf01\Documents\Reset.log log type: text closed on: 27 Sep 2022, 16:54:04 ---------------------------------------------------------------------------------