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Regression AnalysisSA

Regression AnalysisSA - Regression Analysis CT_2 versus...

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Regression Analysis: CT_2 versus Right (F) The regression equation is CT_2 = 85.6 - 0.462 Right (F) Predictor Coef SE Coef T P Constant 85.63 12.52 6.84 0.000 Right (F) -0.4620 0.1778 -2.60 0.019 S = 17.5228 R-Sq = 28.4% R-Sq(adj) = 24.2% PRESS = 6687.29 R-Sq(pred) = 8.30% Analysis of Variance Source DF SS MS F P Regression 1 2072.8 2072.8 6.75 0.019 Residual Error 17 5219.9 307.1 Lack of Fit 15 5021.3 334.8 3.37 0.252 Pure Error 2 198.5 99.3 Total 18 7292.6 15 rows with no replicates Unusual Observations
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Right Obs (F) CT_2 Fit SE Fit Residual St Resid 1 7 91.00 82.44 11.36 8.56 0.64 X 7 93 4.00 42.67 6.17 -38.67 -2.36R R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage. Regression Analysis: CT_2 versus Right (F) The regression equation is CT_2 = 85.6 - 0.462 Right (F) Predictor Coef SE Coef T P Constant 85.63 12.52 6.84 0.000 Right (F) -0.4620 0.1778 -2.60 0.019 S = 17.5228 R-Sq = 28.4% R-Sq(adj) = 24.2% PRESS = 6687.29 R-Sq(pred) = 8.30% Analysis of Variance Source DF SS MS F P Regression 1 2072.8 2072.8 6.75 0.019 Residual Error 17 5219.9 307.1 Lack of Fit 15 5021.3 334.8 3.37 0.252 Pure Error 2 198.5 99.3 Total 18 7292.6 15 rows with no replicates Unusual Observations Right Obs (F) CT_2 Fit SE Fit Residual St Resid 1 7 91.00 82.44 11.36 8.56 0.64 X 7 93 4.00 42.67 6.17 -38.67 -2.36R R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage. Regression Analysis: CT_2 versus Right (F), Right (P) The regression equation is CT_2 = 82.0 - 0.562 Right (F) + 0.151 Right (P) Predictor Coef SE Coef T P Constant 82.04 16.90 4.85 0.000 Right (F) -0.5619 0.3560 -1.58 0.134 Right (P) 0.1510 0.4620 0.33 0.748
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S = 18.0021 R-Sq = 28.9% R-Sq(adj) = 20.0% PRESS = 19652.9 R-Sq(pred) = 0.00% Analysis of Variance Source DF SS MS F P Regression 2 2107.4 1053.7 3.25 0.065 Residual Error 16 5185.2 324.1 Total 18 7292.6 No replicates. Cannot do pure error test. Source DF Seq SS Right (F) 1 2072.8 Right (P) 1 34.6 Unusual Observations Right Obs (F) CT_2 Fit SE Fit Residual St Resid 1 7 91.00 86.78 17.66 4.22 1.22 X 7 93 4.00 43.53 6.87 -39.53 -2.38R R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage. Residual Plots for CT_2 Regression Analysis: CT_2 versus Right (F), Right (P) The regression equation is CT_2 = 82.0 - 0.562 Right (F) + 0.151 Right (P) Predictor Coef SE Coef T P Constant 82.04 16.90 4.85 0.000 Right (F) -0.5619 0.3560 -1.58 0.134 Right (P) 0.1510 0.4620 0.33 0.748 S = 18.0021 R-Sq = 28.9% R-Sq(adj) = 20.0% PRESS = 19652.9 R-Sq(pred) = 0.00% Analysis of Variance Source DF SS MS F P Regression 2 2107.4 1053.7 3.25 0.065 Residual Error 16 5185.2 324.1 Total 18 7292.6 No replicates.
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Cannot do pure error test. Regression Analysis: CT_4 versus Right (F) The regression equation is CT_4 = 75.0 - 0.492 Right (F) Predictor Coef SE Coef T P Constant 74.99 15.15 4.95 0.000 Right (F) -0.4921 0.2152 -2.29 0.035 S = 21.2092 R-Sq = 23.5% R-Sq(adj) = 19.0% PRESS = 10636.7 R-Sq(pred) = 0.00% Analysis of Variance Source DF SS MS F P Regression 1 2351.8 2351.8 5.23 0.035 Residual Error 17 7647.1 449.8 Lack of Fit 15 6932.3 462.2 1.29 0.521 Pure Error 2 714.8 357.4 Total 18 9998.9 15 rows with no replicates Unusual Observations Right Obs (F) CT_4 Fit SE Fit Residual St Resid 1 7 102.00 71.60 13.75 30.40 1.88 X X denotes an observation whose X value gives it large leverage. Source DF Seq SS Right (F) 1 2072.8 Right (P) 1 34.6 Unusual Observations Right Obs (F) CT_2 Fit SE Fit Residual St Resid 1 7 91.00 86.78 17.66 4.22 1.22 X 7 93 4.00 43.53 6.87 -39.53 -2.38R R denotes an observation with a large standardized residual.
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