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February 08, 2005
Basketball Data - II
------------------------------------------------------------------------------------------------------ log: T:\170\class2.log log type: text opened on: 8 Feb 2005, 11:10:15 . 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 ------------------------------------------------------------------------------ . summarize diff2 diff1 Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- diff2 | 16 -1.6875 7.972609 -14 17 diff1 | 16 4.8125 8.596269 -9 20 . tabulate win1 at, summarize(win) Means, Standard Deviations and Frequencies of win | at win1 | 0 1 | Total -----------+----------------------+---------- 0 | .33333333 0 | .2 | .57735027 0 | .4472136 | 3 2 | 5 -----------+----------------------+---------- 1 | 1 .33333333 | .63636364 | 0 .51639778 | .50452498 | 5 6 | 11 -----------+----------------------+---------- Total | .75 .25 | .5 | .46291005 .46291005 | .51639778 | 8 8 | 16 . tabulate win1 at, summarize(win) nomeans nostandard Frequencies of win | at win1 | 0 1 | Total -----------+----------------------+---------- 0 | 3 2 | 5 1 | 5 6 | 11 -----------+----------------------+---------- Total | 8 8 | 16 . tabulate win1 at, summarize(win) nostandard Means and Frequencies of win | at win1 | 0 1 | Total -----------+----------------------+---------- 0 | .33333333 0 | .2 | 3 2 | 5 -----------+----------------------+---------- 1 | 1 .33333333 | .63636364 | 5 6 | 11 -----------+----------------------+---------- Total | .75 .25 | .5 | 8 8 | 16 . - preserve - sort at - restore . tabulate diff at, summarize(win) nostandard Means and Frequencies of win | at diff | 0 1 | Total -----------+----------------------+---------- -11 | . 0 | 0 | 0 1 | 1 -----------+----------------------+---------- -9 | . 0 | 0 | 0 1 | 1 -----------+----------------------+---------- -6 | . 0 | 0 | 0 1 | 1 -----------+----------------------+---------- -5 | . 0 | 0 | 0 1 | 1 -----------+----------------------+---------- -2 | . 0 | 0 | 0 1 | 1 -----------+----------------------+---------- 0 | 0 0 | 0 | 2 1 | 3 -----------+----------------------+---------- 2 | 1 . | 1 | 1 0 | 1 -----------+----------------------+---------- 6 | . 1 | 1 | 0 1 | 1 -----------+----------------------+---------- 7 | 1 1 | 1 | 1 1 | 2 -----------+----------------------+---------- 11 | 1 . | 1 | 1 0 | 1 -----------+----------------------+---------- 15 | 1 . | 1 | 1 0 | 1 -----------+----------------------+---------- 16 | 1 . | 1 | 1 0 | 1 -----------+----------------------+---------- 19 | 1 . | 1 | 1 0 | 1 -----------+----------------------+---------- Total | .75 .25 | .5 | 8 8 | 16 . tabulate win1 at, summarize(diff) nostandard Means and Frequencies of diff | at win1 | 0 1 | Total -----------+----------------------+---------- 0 | .66666667 -10 | -3.6 | 3 2 | 5 -----------+----------------------+---------- 1 | 13.6 0 | 6.1818182 | 5 6 | 11 -----------+----------------------+---------- Total | 8.75 -2.5 | 3.125 | 8 8 | 16 . 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 ------------------------------------------------------------------------------ . regress diff win1 Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 1, 14) = 5.22 Model | 328.913636 1 328.913636 Prob > F = 0.0385 Residual | 882.836364 14 63.0597403 R-squared = 0.2714 -------------+------------------------------ Adj R-squared = 0.2194 Total | 1211.75 15 80.7833333 Root MSE = 7.941 ------------------------------------------------------------------------------ diff | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- win1 | 9.781818 4.283066 2.28 0.039 .5955559 18.96808 _cons | -3.6 3.55133 -1.01 0.328 -11.21685 4.016846 ------------------------------------------------------------------------------ . regress diff win1 at Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 2, 13) = 25.13 Model | 962.712963 2 481.356481 Prob > F = 0.0000 Residual | 249.037037 13 19.1566952 R-squared = 0.7945 -------------+------------------------------ Adj R-squared = 0.7629 Total | 1211.75 15 80.7833333 Root MSE = 4.3768 ------------------------------------------------------------------------------ diff | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- win1 | 11.62963 2.382448 4.88 0.000 6.482664 16.7766 at | -12.7037 2.208588 -5.75 0.000 -17.47507 -7.932339 _cons | 1.481481 2.147509 0.69 0.502 -3.157931 6.120894 ------------------------------------------------------------------------------ . 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 ------------------------------------------------------------------------------ . 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 diff2 diff1 at Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 2, 13) = 7.91 Model | 523.404537 2 261.702268 Prob > F = 0.0057 Residual | 430.032963 13 33.0794587 R-squared = 0.5490 -------------+------------------------------ Adj R-squared = 0.4796 Total | 953.4375 15 63.5625 Root MSE = 5.7515 ------------------------------------------------------------------------------ diff2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- diff1 | -.4924605 .1758791 -2.80 0.015 -.8724242 -.1124969 at | -9.663939 2.927789 -3.30 0.006 -15.98904 -3.338835 _cons | 5.514436 2.322087 2.37 0.034 .4978725 10.531 ------------------------------------------------------------------------------ . regress diff2 nc1 opp1 at Source | SS df MS Number of obs = 16 -------------+------------------------------ F( 3, 12) = 5.56 Model | 554.659824 3 184.886608 Prob > F = 0.0126 Residual | 398.777676 12 33.231473 R-squared = 0.5817 -------------+------------------------------ Adj R-squared = 0.4772 Total | 953.4375 15 63.5625 Root MSE = 5.7647 ------------------------------------------------------------------------------ diff2 | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- nc1 | -.585921 .2009048 -2.92 0.013 -1.023655 -.148187 opp1 | .3727066 .2152286 1.73 0.109 -.0962363 .8416495 at | -9.956003 2.949921 -3.38 0.006 -16.38333 -3.528677 _cons | 13.73266 8.787856 1.56 0.144 -5.414432 32.87975 ------------------------------------------------------------------------------ . exit, clear
Posted by bparke at February 8, 2005 07:38 PM