------------------------------------------------------------------------------- log: d:\bill\fall2008\econ30331\class_size_1.log log type: text opened on: 10 Sep 2008, 10:15:12 . . * open class_size_1, 420 observations from . * california k-6 and k-8 schools . * 6th grad test scores . use ca_school_data_2 . . * get means of key variables . sum average_score student_teacher esl_pct Variable | Obs Mean Std. Dev. Min Max -------------+-------------------------------------------------------- average_sc~e | 420 654.1565 19.05335 605.55 706.75 student_te~r | 420 19.64043 1.891812 14 25.8 esl_pct | 420 15.76816 18.28593 0 85.53972 . . * get correlations between key variables . corr average_score student_teacher esl_pct (obs=420) | averag~e studen~r esl_pct -------------+--------------------------- average_sc~e | 1.0000 student_te~r | -0.2264 1.0000 esl_pct | -0.6441 0.1876 1.0000 . . * run regression with one variable . reg average_score student_teacher Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 1, 418) = 22.58 Model | 7794.11004 1 7794.11004 Prob > F = 0.0000 Residual | 144315.484 418 345.252353 R-squared = 0.0512 -------------+------------------------------ Adj R-squared = 0.0490 Total | 152109.594 419 363.030056 Root MSE = 18.581 ------------------------------------------------------------------------------ average_sc~e | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- student_te~r | -2.279808 .4798256 -4.75 0.000 -3.22298 -1.336637 _cons | 698.933 9.467491 73.82 0.000 680.3231 717.5428 ------------------------------------------------------------------------------ . . * run synthetic regression of esl_pct on . * student_teacher . reg esl_pct student_teacher Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 1, 418) = 15.25 Model | 4932.98526 1 4932.98526 Prob > F = 0.0001 Residual | 135170.2 418 323.373684 R-squared = 0.0352 -------------+------------------------------ Adj R-squared = 0.0329 Total | 140103.185 419 334.375143 Root MSE = 17.983 ------------------------------------------------------------------------------ esl_pct | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- student_te~r | 1.813719 .4643735 3.91 0.000 .9009206 2.726517 _cons | -19.85405 9.162604 -2.17 0.031 -37.86458 -1.843531 ------------------------------------------------------------------------------ . . * run multivariate regression . reg average_score student_teacher esl_pct Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 2, 417) = 155.01 Model | 64864.3011 2 32432.1506 Prob > F = 0.0000 Residual | 87245.2925 417 209.221325 R-squared = 0.4264 -------------+------------------------------ Adj R-squared = 0.4237 Total | 152109.594 419 363.030056 Root MSE = 14.464 ------------------------------------------------------------------------------ average_sc~e | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- student_te~r | -1.101296 .3802783 -2.90 0.004 -1.848797 -.3537945 esl_pct | -.6497768 .0393425 -16.52 0.000 -.7271112 -.5724423 _cons | 686.0322 7.411312 92.57 0.000 671.4641 700.6004 ------------------------------------------------------------------------------ . . . * demonstrate the partialing out . * nature of mv regressions . . * run a regression of STR on ESL . * output the residuals . reg student_teacher esl Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 1, 418) = 15.25 Model | 52.7997281 1 52.7997281 Prob > F = 0.0001 Residual | 1446.78109 418 3.46119878 R-squared = 0.0352 -------------+------------------------------ Adj R-squared = 0.0329 Total | 1499.58082 419 3.57895184 Root MSE = 1.8604 ------------------------------------------------------------------------------ student_te~r | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- esl_pct | .019413 .0049704 3.91 0.000 .0096429 .029183 _cons | 19.33432 .1199307 161.21 0.000 19.09858 19.57006 ------------------------------------------------------------------------------ . . * output residuals . predict res_str, residual . . * run a regression of test scores . * on the student_teacher residuals . reg average_score res_str Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 1, 418) = 4.88 Model | 1754.73229 1 1754.73229 Prob > F = 0.0277 Residual | 150354.861 418 359.700625 R-squared = 0.0115 -------------+------------------------------ Adj R-squared = 0.0092 Total | 152109.594 419 363.030056 Root MSE = 18.966 ------------------------------------------------------------------------------ average_sc~e | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- res_str | -1.101296 .4986194 -2.21 0.028 -2.08141 -.1211819 _cons | 654.1565 .9254351 706.86 0.000 652.3375 655.9756 ------------------------------------------------------------------------------ . . . * close log file . log close log: d:\bill\fall2008\econ30331\class_size_1.log log type: text closed on: 10 Sep 2008, 10:15:12 -------------------------------------------------------------------------------