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consider the following three data sets, in which the variables of interest are x -commuting distance and y - commuting time. Based on the values in the table below, which simple linear regression would be most effective, and why? Model 1 Model 2 Model 3 X Y X Y 15 42 16 16 35 10 32 10 16 17 45 15 44 15 22 18 42 20 45 20 23 19 49 25 63 25 31 20 46 50 115 50 60 coeff p-value coeff p-value coeff p-value Bo 1.6857 0.0001 2.14 0.005 1.13 0.0002 B1 13.66 0.0000 7.86 0.1 3.2 0.0005 SST 114.83 5897.5 1627.33 SSE 65.10 65.1 14.48 MG-20240428-WAO... owner A regression analysis predicts the undrained shear strength (kPa) of sandy soil based on depth (m) and water content ($6). Assess the current model based on goodness-of-fit and significance of coefficients. Additionally, propose improvements if necessary. (Need to show TWO assessments; one for the coefficients and another for the goodness-of fit) Use cr - 5%. Shear Water Strength Content Depth (Kpa) (9%) (m) 14.70 31.50 8.90 SUMMARY OUTPUT 48.00 27.00 36.60 25.60 25.90 36.80 Regression Statistics 10.00 39.10 6.10 Multiple R 0.67 16.00 39.20 6.90 R Square 0.45 16.80 38.30 6.90 Standard Error 9.02 20.70 33.90 7.30 Observations 14.00 38.80 33.80 8.40 16.90 27.90 6.50 Standard Coefficients Error * Stat P-value 27.00 33.10 8.00 22.9252 0.6210 0.5473 16.00 26.30 4.50 Intercept 14.2366 0.2724 2.4415 0.0327 24.90 37.80 9.90 Depth (m) 0.6652 0.9875 7.30 34.60 2.90 Water Content (%) -0.0102 0.6321 -0.0161 12.80 36.40 2.00