Question 14 4 pts Consistent with the first step of choosing our "best" model, provide each of the following for a test of curvature Practical interpretation: There is sufficient evidence (at alpha = 5%) of curvature in the relationship between cubic feet moved (x1) and elevator status (x2) There is insufficient evidence lat alpha = 5%) of interaction in the relationship between between labor hours (M) and cubic feet moved (1) There is sufficient evidence (at alpha - 5%) of interaction in the relationship between labor hours (and cubic feet moved (x1) There is insufficient evidence lat alpha - 5%) of curvature in the relationship between labor hours () and cubic feet moved (x1) There is sufficient evidence (at alpha - 5%) of curvature in the relationship between labor hours (y) and cubic feet moved (1) Question 15 4 pts MacBook Pro D Q Search or type URL + 5 6 8 7 8 C 9 R T Y U I Consistent with the second step of choosing our best model provide each of the following for a test of interaction Null Hypothesis Note: Betas are exactly as they were in our best model process HB 0 H - As = 0 Ho Bes=0 Question 16 4 pts Constant with the cacandon of choosinn our "hac model residench the following for tact MacBook Pro Q o Q Search or type URL R $ 5 0) 8 7 + 00 9 R T U 200 600 1000 1400 CUBFT PO #3 Correlations (Pearson) ELEV HOURS CUBET ELEV HOURS CUBFT 1.0000 0.9430 1.0000 -0.3847 -0.2895 1.0000 Cases Included 36 Missing Cases O PO #4 MacBook Pro 0 Q Search or type URL $ 4 96 5 6 7 + 0 C 9 R T Y 0 PO #4 Least Squares Linear Regression of HOURS Predictor Variables Constant CUBET ELEV CUBF EL CUBFSQ CUBFSQ_EL Coefficient 11.6812 0.01468 -6.30474 0.01152 2.305E-05 -9.458E-06 Std Error 17.3608 0.04404 18.2770 0.04830 2.368E-05 2.825E-05 T 0.67 0.33 -0.34 0.24 0.97 -0.33 P 0.5062 0.7411 0.7325 0.8132 0.3380 0.7402 VIE 0.0 263.1 92.7 412.4 177.2 143.0 R4 Adjusted R. AICC PRESS 0.9216 0.9085 119.85 932.52 Mean Square Error (MSE) Standard Deviation 20.3168 4.50742 Source Regression Residual Total DF 5 30 35 SS 7161.93 609.50 7771.44 MS 1432.39 20.3168 F 70.50 P 0.0000 Lack of Fit Pure Error 29 1 609.38 0.13 21.0131 0.12500 168.10 0.0609 Cases Included 36 Missing Cases 0 MacBook Pro C Q Search or type URL $ %6 5 6 & 7 8 9 R T Y U I O Cases Included 36 Missing cases o PO #5 Best Sabset Regression Models for HOURS Forced Independent Variables: (A) CUBFT (B) ELEV (C) CUBF_EL Unforced Independent Variables: (D) CUBFSQ (E) CUBFSQ_EL Adjusted AICO - PCP R Square Min AICC 4 3.7 0.9093 115.86 5 0.9111 116.88 5 4.9 0.9087 117.87 6 6.0 0.9085 119.85 Resid ss 644.545 611.781 628.763 609.505 PP(P) Model Variables 1.66 0.2071 ABCD 0.78 0.3845 A BCE 0.86 0.4324 ABCDE Cases Included 36 Missing Cases o MacBook Pro c D Q Search or type URL B $ A 4 C 5 8 7 0) 8 9 R T U 0 PO N6 Least squares Linear regression of HOURS Predictor Variables Constant CUBFT ELEV CUBF EL Coefficient -4.72596 0.05731 5.46138 -0.01390 Std Error 4.15342 4.800E-03 4.70451 5.9412-03 T -1.14 11.92 1.16 -2.34 P 0.2636 0.0000 0.2543 0.0257 VIF 0.0 3.2 6.2 6.3 R. Adjusted R. AICC PRESS 0.9171 0.9093 115.86 874.11 Mean Square Error (MSE) Standard Deviation 20.1420 4.48799 SS Source Regression Residual Total DF 3 32 35 MS 2375.63 20.1420 P 117.94 P 0.0000 7126.89 644.54 7771.44 Lack of Fit Pure Error 31 2 644.42 0.13 20.7877 0.12500 166.30 0.0613 Cases Included 36 Missing Cases o MacBook Pro D Q Search or type URL t 4 012