HERE ARE THE REGRESSION RESULTS FOR THE CALIFORNIA SCHOOLS DATA (QUESTION #1) . regress testscr str elpct 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 ------------------------------------------------------------------------------ testscr | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- str | -1.101296 .3802783 -2.90 0.004 -1.848797 -.3537946 elpct | -.6497768 .0393425 -16.52 0.000 -.7271112 -.5724423 _cons | 686.0322 7.411312 92.57 0.000 671.4641 700.6004 ------------------------------------------------------------------------------ HERE IS THE SECOND PART OF THE REGRESSION - NOTE THAT THE COEFFICIENT ON EXPENSTU IS THE COEFFICIENT IN THE TEXT/1000. . regress testscr expenstu str elpct Source | SS df MS Number of obs = 420 -------------+------------------------------ F( 3, 416) = 107.45 Model | 66409.8837 3 22136.6279 Prob > F = 0.0000 Residual | 85699.7099 416 206.008918 R-squared = 0.4366 -------------+------------------------------ Adj R-squared = 0.4325 Total | 152109.594 419 363.030056 Root MSE = 14.353 ------------------------------------------------------------------------------ testscr | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- expenstu | .0038679 .0014121 2.74 0.006 .0010921 .0066437 str | -.2863992 .4805232 -0.60 0.551 -1.230955 .658157 elpct | -.6560227 .0391059 -16.78 0.000 -.7328924 -.5791529 _cons | 649.5779 15.20572 42.72 0.000 619.6883 679.4676 ------------------------------------------------------------------------------ HERE ARE THE REGRESSION RESULTS FOR THE HOUSE PRICE DATA regress price sqrft bdrms Source | SS df MS Number of obs = 88 -------------+------------------------------ F( 2, 85) = 72.96 Model | 580009.152 2 290004.576 Prob > F = 0.0000 Residual | 337845.354 85 3974.65122 R-squared = 0.6319 -------------+------------------------------ Adj R-squared = 0.6233 Total | 917854.506 87 10550.0518 Root MSE = 63.045 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- sqrft | .1284362 .0138245 9.29 0.000 .1009495 .1559229 bdrms | 15.19819 9.483517 1.60 0.113 -3.657582 34.05396 _cons | -19.315 31.04662 -0.62 0.536 -81.04399 42.414 ------------------------------------------------------------------------------