'Xray','BedDays','Length','Hours' 2463, 472.92, 4.45, 566.52 2048, 1339.75, 6.92, 696.82 3940, 620.25, 4.28, 1033.15 6505, 568.33, 3.9, 1603.62 5723, 1497.6, 5.5, 1611.37 11520, 1365.83, 4.6, 1613.27 5779, 1687, 5.62, 1854.17 5969, 1639.92, 5.15, 2160.55 8461, 2872.33, 6.18, 2305.58 20106, 3655.08, 6.15, 3503.93 13313, 2912, 5.88, 3571.89 10771, 3921, 4.88, 3741.4 15543, 3865.67, 5.5, 4026.52 36194, 7684. 1,7, 10343.81 34703, 12446.33, 10.78, 11732.17 39204, 14098.4, 7.05, 15414.94 86533, 15524, 6.35, 18854.4

1. Create 3 simple regression models that predict the number of hours spent in the hospital depending on either one of the 3 variables left in the data.

2. Compare the P-values of the above models. Select the model (variable) with the lowest P-value (less than 5%).

3. Create 2 multiple regression models consisting on the variable you have identified in the previous step and one of the remaining two.

4. Compare the P-values of the above model and select which one is preferable depending on the P-values of their coefficients.

5. Create a model that includes all variables. Which one of the models you have created is the one you would use for prediction.

Subject | Mathematics |

Due By (Pacific Time) | 10/15/2015 12:00 am |

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