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February 03, 2005
Basketball Data - I
-------------------------------------------------------------------------------------------------------- log: T:\170\class1.log log type: text opened on: 3 Feb 2005, 11:40:28 . summarize Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- n | 16 8.5 4.760952 1 16 game | 0 at | 16 .5 .5163978 0 1 nc1 | 16 40.5625 8.421946 26 55 nc2 | 16 38.875 7.228416 29 54 -------------+-------------------------------------------------------- opp1 | 16 35.75 7.715785 18 47 opp2 | 16 40.5625 6.791846 28 54 nc | 16 79.4375 11.26037 65 103 opp | 16 76.3125 10.35193 53 90 diff | 16 3.125 8.987955 -11 19 -------------+-------------------------------------------------------- diff1 | 16 4.8125 8.596269 -9 20 diff2 | 16 -1.6875 7.972609 -14 17 win | 16 .5 .5163978 0 1 win1 | 16 .6875 .4787136 0 1 win2 | 16 .375 .5 0 1 . twoway (scatter opp nc) . regress opp nc Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 10.63 Model | 693.90827 1 693.90827 Prob > F = 0.0057 Residual | 913.52923 14 65.2520879 R-squared = 0.4317 -------------+------------------------------ Adj R-squared = 0.3911 Total | 1607.4375 15 107.1625 Root MSE = 8.0779 ------------------------------------------------------------------------------ opp | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- nc | .6040222 .1852248 3.26 0.006 .2067546 1.00129 _cons | 28.33049 14.85173 1.91 0.077 -3.523314 60.18428 ------------------------------------------------------------------------------ . regress nc opp Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 10.63 Model | 821.039798 1 821.039798 Prob > F = 0.0057 Residual | 1080.8977 14 77.2069787 R-squared = 0.4317 -------------+------------------------------ Adj R-squared = 0.3911 Total | 1901.9375 15 126.795833 Root MSE = 8.7868 ------------------------------------------------------------------------------ nc | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- opp | .7146856 .21916 3.26 0.006 .2446343 1.184737 _cons | 24.89805 16.86829 1.48 0.162 -11.28083 61.07693 ------------------------------------------------------------------------------ . correlate no observations r(2000); . - preserve . correlate nc nc1 nc2 opp opp1 opp2 (obs=16) | nc nc1 nc2 opp opp1 opp2 -------------+------------------------------------------------------ nc | 1.0000 nc1 | 0.7670 1.0000 nc2 | 0.6642 0.0297 1.0000 opp | 0.6570 0.6058 0.3177 1.0000 opp1 | 0.3988 0.4352 0.1142 0.7547 1.0000 opp2 | 0.5484 0.4288 0.3546 0.6668 0.0143 1.0000 . regress nc2 nc1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 0.01 Model | .691549668 1 .691549668 Prob > F = 0.9130 Residual | 783.05845 14 55.9327465 R-squared = 0.0009 -------------+------------------------------ Adj R-squared = -0.0705 Total | 783.75 15 52.25 Root MSE = 7.4788 ------------------------------------------------------------------------------ nc2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- nc1 | .0254949 .2292847 0.11 0.913 -.4662718 .5172616 _cons | 37.84086 9.486437 3.99 0.001 17.49448 58.18725 ------------------------------------------------------------------------------ . regress opp2 opp1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 0.00 Model | .141727324 1 .141727324 Prob > F = 0.9580 Residual | 691.795773 14 49.4139838 R-squared = 0.0002 -------------+------------------------------ Adj R-squared = -0.0712 Total | 691.9375 15 46.1291667 Root MSE = 7.0295 ------------------------------------------------------------------------------ opp2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- opp1 | .012598 .2352335 0.05 0.958 -.4919277 .5171237 _cons | 40.11212 8.591258 4.67 0.000 21.68571 58.53854 ------------------------------------------------------------------------------ . twoway (scatter nc2 nc1) . twoway (scatter opp2 opp1) . twoway (scatter nc2 nc1) . regress nc nc1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 20.00 Model | 1118.87905 1 1118.87905 Prob > F = 0.0005 Residual | 783.05845 14 55.9327465 R-squared = 0.5883 -------------+------------------------------ Adj R-squared = 0.5589 Total | 1901.9375 15 126.795833 Root MSE = 7.4788 ------------------------------------------------------------------------------ nc | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- nc1 | 1.025495 .2292847 4.47 0.001 .5337282 1.517262 _cons | 37.84086 9.486437 3.99 0.001 17.49448 58.18725 ------------------------------------------------------------------------------ . regress opp opp1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 18.53 Model | 915.641727 1 915.641727 Prob > F = 0.0007 Residual | 691.795773 14 49.4139838 R-squared = 0.5696 -------------+------------------------------ Adj R-squared = 0.5389 Total | 1607.4375 15 107.1625 Root MSE = 7.0295 ------------------------------------------------------------------------------ opp | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- opp1 | 1.012598 .2352335 4.30 0.001 .5080723 1.517124 _cons | 40.11212 8.591258 4.67 0.000 21.68571 58.53854 ------------------------------------------------------------------------------ . twoway (scatter nc1 nc) . twoway (scatter nc nc1) . twoway (scatter opp opp1) . regress diff2 diff1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 2.89 Model | 163.002541 1 163.002541 Prob > F = 0.1114 Residual | 790.434959 14 56.4596399 R-squared = 0.1710 -------------+------------------------------ Adj R-squared = 0.1117 Total | 953.4375 15 63.5625 Root MSE = 7.514 ------------------------------------------------------------------------------ diff2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- diff1 | -.383479 .2256906 -1.70 0.111 -.8675372 .1005792 _cons | .1579927 2.169889 0.07 0.943 -4.495957 4.811942 ------------------------------------------------------------------------------ . regress diff diff1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 7.46 Model | 421.315041 1 421.315041 Prob > F = 0.0162 Residual | 790.434959 14 56.4596399 R-squared = 0.3477 -------------+------------------------------ Adj R-squared = 0.3011 Total | 1211.75 15 80.7833333 Root MSE = 7.514 ------------------------------------------------------------------------------ diff | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- diff1 | .616521 .2256906 2.73 0.016 .1324628 1.100579 _cons | .1579927 2.169889 0.07 0.943 -4.495957 4.811942 ------------------------------------------------------------------------------ . twoway (scatter diff diff1) . regress diff at Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 10.05 Model | 506.25 1 506.25 Prob > F = 0.0068 Residual | 705.5 14 50.3928571 R-squared = 0.4178 -------------+------------------------------ Adj R-squared = 0.3762 Total | 1211.75 15 80.7833333 Root MSE = 7.0988 ------------------------------------------------------------------------------ diff | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- at | -11.25 3.549396 -3.17 0.007 -18.8627 -3.637302 _cons | 8.75 2.509802 3.49 0.004 3.36701 14.13299 ------------------------------------------------------------------------------ . table at, contents( mean nc mean op mean diff ) op ambiguous abbreviation r(111); . table at, contents( mean nc mean opp mean diff ) ---------------------------------------------- at | mean(nc) mean(opp) mean(diff) ----------+----------------------------------- 0 | 84.125 75.375 8.75 1 | 74.75 77.25 -2.5 ---------------------------------------------- . log close log: T:\170\class1.log log type: text closed on: 3 Feb 2005, 12:14:56 ------------------------------------------------------------------------------------------------------
Posted by bparke at February 3, 2005 07:35 PM