14 1 point The data have information from boxscores from all 82 regular season basketball games...

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14 1 point The data have information from boxscores from all 82 regular season basketball games played by the Miami Heat NBA team in the 2010-11 season. Multiple regression output is shown for predicting the number of points scored by the Miami Heat in a game based on the number of rebounds, steals, blocks, and assists in the game. The regression equation is Points = 64.7 + 0.216 Rebounds - 0.068 Steals + 0.839 Blocks + 1.22 Assists Predictor Constant 64.655 Rebounds 0.2156 Steals -0.0676 Coef SE Coef 9.724 6.65 0.000 0.2019 1.07 0.289 0.4448 -0.15 0.880 T P Blocks Assists 0.8389 0.4671 1.2192 0.2298 1.80 0.076 5.30 0.000 S = 9.76719 R-Sq = 29.9% R-Sq (adj) = 26.3% How might we proceed if we want to try to improve this model? Remove the variable Blocks from the model. Remove the variable Steals from the model. Remove the Constant from the model. Remove the variable Rebounds from the model. Remove the variable Assists from the model. Previous Next 14 1 point The data have information from boxscores from all 82 regular season basketball games played by the Miami Heat NBA team in the 2010-11 season. Multiple regression output is shown for predicting the number of points scored by the Miami Heat in a game based on the number of rebounds, steals, blocks, and assists in the game. The regression equation is Points = 64.7 + 0.216 Rebounds - 0.068 Steals + 0.839 Blocks + 1.22 Assists Predictor Constant 64.655 Rebounds 0.2156 Steals -0.0676 Coef SE Coef 9.724 6.65 0.000 0.2019 1.07 0.289 0.4448 -0.15 0.880 T P Blocks Assists 0.8389 0.4671 1.2192 0.2298 1.80 0.076 5.30 0.000 S = 9.76719 R-Sq = 29.9% R-Sq (adj) = 26.3% How might we proceed if we want to try to improve this model? Remove the variable Blocks from the model. Remove the variable Steals from the model. Remove the Constant from the model. Remove the variable Rebounds from the model. Remove the variable Assists from the model. Previous Next