Homework Answers
Solution
No, this model is not best
Because
1) From anova the p-value = 0.695 > 0.05 level of significance which indicates that size variable that is independent variable not significant.
2) The R –square = 0.0032 which very less it should greater than 0.8
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Is this the best model?
Least Squares Linear Regression of Rent P Predictor Variables Constant Size...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Coefficient 1276.56 0.16486 Std Error 454.843...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Coefficient 1276.56 0.16486 Std Error 454.843 0.41717 T 2.81 0.40 P 0.0072 0.6945 Mean Square Error (MSE) Standard Deviation 458532 677.150 R2 Adjusted R2 AICC PRESS 0.0032 -0.0175 656.27 2.34E+07 DF F 0.16 P 0.6945 1 Source Regression Residual Total MS 71610.6 458532 SS 71610.6 2.201E+07 2.208E+07 48 49 20.14 0.0006 Lack of Fit Pure Error 42 6 2.185E+07 155000 520346 25833.3 Cases Included 50 Missing Cases 0 7. Identify...
Is this the best model? Least Squares Linear Regression of Rent Predictor Variables Constant Size Location...
Is this the best model?
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location Coefficient 1260.79 0.08977 191.625 Std Error 455.277 0.42423 194.769 T 2.77 0.21 0.98 P 0.0080 0.8333 0.3302 VIF 0.0 1.0 1.0 Mean Square Error (MSE) Standard Deviation 458838 677.376 RS Adjusted R AICC PRESS 0.0234 -0.0182 657.62 2.38E+07 DF F 0.56 P 0.5738 2 Source Regression Residual Total MS 257878 458838 SS 515756 2.157E+07 2.208E+07 47 49 45 M M Lack of Fit Pure...
how would I figure out the best regression model? Least Squares Linear Regression of Rent Predictor...
how would I figure out the best regression model?
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location Coefficient 1260.79 0.08977 191.625 Std Error 455.277 0.42423 194.769 T 2.77 0.21 0.98 P 0.0080 0.8333 0.3302 VIF 0.0 1.0 1.0 Mean Square Error (MSE) Standard Deviation 458838 677.376 RS Adjusted R AICC PRESS 0.0234 -0.0182 657.62 2.38E+07 DF F 0.56 P 0.5738 2 Source Regression Residual Total MS 257878 458838 SS 515756 2.157E+07 2.208E+07 47 49 45 M M...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location X1X2 Coefficient 1532.52 -0.17545 -332.138...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location X1X2 Coefficient 1532.52 -0.17545 -332.138 0.49286 Std Error 658.456 0.62872 931.704 0.85707 T 2.33 -0.28 -0.36 0.58 P 0.0244 0.7814 0.7231 0.5681 VIF 0.0 2.2 23.3 26.3 R2 Adjusted R2 AICC PRESS Mean Square Error (MSE) Standard Deviation 465466 682.251 0.0303 -0.0329 659.73 2.41E+07 F 0.48 Source Regression Residual Total P 0.6981 DF 3 46 49 MS 223225 465466 SS 669676 2.141E+07 2.208E+07 M Lack of Fit Pure Error...
C. Interaction Test (8 points) - Fill in the following information for your test. Full Model:...
C. Interaction Test (8 points) - Fill in the following information for your test. Full Model: Reduced Model: Test: Ho: Ha: Test Statistic: P-value: Conclusion: Least Squares Linear Regression of Rent Predictor Variables Constant Size Location X1X2 Coefficient 1532.52 -0.17545 -332.138 0.49286 Std Error 658.456 0.62872 931.704 0.85707 T 2.33 -0.28 -0.36 0.58 P 0.0244 0.7814 0.7231 0.5681 VIF 0.0 2.2 23.3 26.3 Mean Square Error (MSE) Standard Deviation 465466 682.251 R2 Adjusted R AIS DPRESS 0.0303 -0.0329 659.73 2.41E+07...
5. Model Building: For the first three tests that you conducted (the Global F-test, the quadratics...
5. Model Building: For the first three tests that you conducted (the Global F-test, the quadratics test, and the interaction test), provide the information that I ask for in the space below. In addition, for each test, include the printout used in the appropriate space. A.) Global F-test (6 points) Complete 2nd-Order Model: E(y) = β0 + β1x1 + β2x12 + β3x2 + β4x1x2 + β5x12x2 Fill in the following information for your test: Test: Ho:__________ Ha: __________ Test Statistic:...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Coefficient 1276.56 0.16486 Std Error 454.843 0.41717 T 2.81 0.40 P 0.0072 0.6945 Mean Square Error (MSE) Standard Deviation 458532 677.150 R2 Adjusted R2 AICC PRESS 0.0032 -0.0175 656.27 2.34E+07 DF F 0.16 P 0.6945 1 Source Regression Residual Total MS 71610.6 458532 SS 71610.6 2.201E+07 2.208E+07 48 49 20.14 0.0006 Lack of Fit Pure Error 42 6 2.185E+07 155000 520346 25833.3 Cases Included 50 Missing Cases 0 7. Identify...
Is this the best model?
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location Coefficient 1260.79 0.08977 191.625 Std Error 455.277 0.42423 194.769 T 2.77 0.21 0.98 P 0.0080 0.8333 0.3302 VIF 0.0 1.0 1.0 Mean Square Error (MSE) Standard Deviation 458838 677.376 RS Adjusted R AICC PRESS 0.0234 -0.0182 657.62 2.38E+07 DF F 0.56 P 0.5738 2 Source Regression Residual Total MS 257878 458838 SS 515756 2.157E+07 2.208E+07 47 49 45 M M Lack of Fit Pure...
how would I figure out the best regression model?
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location Coefficient 1260.79 0.08977 191.625 Std Error 455.277 0.42423 194.769 T 2.77 0.21 0.98 P 0.0080 0.8333 0.3302 VIF 0.0 1.0 1.0 Mean Square Error (MSE) Standard Deviation 458838 677.376 RS Adjusted R AICC PRESS 0.0234 -0.0182 657.62 2.38E+07 DF F 0.56 P 0.5738 2 Source Regression Residual Total MS 257878 458838 SS 515756 2.157E+07 2.208E+07 47 49 45 M M...
Least Squares Linear Regression of Rent Predictor Variables Constant Size Location X1X2 Coefficient 1532.52 -0.17545 -332.138 0.49286 Std Error 658.456 0.62872 931.704 0.85707 T 2.33 -0.28 -0.36 0.58 P 0.0244 0.7814 0.7231 0.5681 VIF 0.0 2.2 23.3 26.3 R2 Adjusted R2 AICC PRESS Mean Square Error (MSE) Standard Deviation 465466 682.251 0.0303 -0.0329 659.73 2.41E+07 F 0.48 Source Regression Residual Total P 0.6981 DF 3 46 49 MS 223225 465466 SS 669676 2.141E+07 2.208E+07 M Lack of Fit Pure Error...
C. Interaction Test (8 points) - Fill in the following information for your test. Full Model: Reduced Model: Test: Ho: Ha: Test Statistic: P-value: Conclusion: Least Squares Linear Regression of Rent Predictor Variables Constant Size Location X1X2 Coefficient 1532.52 -0.17545 -332.138 0.49286 Std Error 658.456 0.62872 931.704 0.85707 T 2.33 -0.28 -0.36 0.58 P 0.0244 0.7814 0.7231 0.5681 VIF 0.0 2.2 23.3 26.3 Mean Square Error (MSE) Standard Deviation 465466 682.251 R2 Adjusted R AIS DPRESS 0.0303 -0.0329 659.73 2.41E+07...
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