A cost estimator for a construction company has collected the data below describing the total cost (Y)
Question:
A cost estimator for a construction company has collected the data below describing the total cost (Y) of 97 different projects and the following five independent variables thought to exert relevant influence on the total cost:
regular or premium wages paid total units of work required contracted units of work per day level of equipment required city/location of work The cost estimator would like to develop a regression model to predict the total cost of a project as a function of these five independent variables.
1) Which combination of the independent variables would you suggest the estimator use? What is the estimated regression equation for this model? (Round your numerical values to two decimal places.)
What is its adjusted-R2 value? (Round your answer to four decimal places.)
2) Suppose the estimator wants to use total units of work (X2) and city/location of work (X5)
as the only independent variables for the regression model to predict total cost. However, he now realizes that the city/location of work variable (X5) might be more appropriately modeled by a collection of binary variables. Modify the data set to include the necessary binary variables. Because there are six distinct city/location values, five binary variables would be needed. Assume the sixth city/location should be represented by values of zero for all the binary variables.
Which combination of the new set of six independent variables (i.e., X2 plus the five binary variables representing X5) would you now suggest the estimator use? What is the estimated regression equation for this model? (Enter your answer using X6 as the binary variable for City 1, X7 as the binary variable for City 2, X8 as the binary variable for City 3, X9 as the binary variable for City 4, and X10 as the binary variable for City 5. Round your numerical values to two decimal places.)
What is its adjusted R2 value? (Round your answer to four decimal places.)
| Wage - Regular (0) or Premium (1) | Units of Work | Contracted Units per Day | Level of Equipment Required | City | Total Cost (Y) |
| 0 | 52 | 5 | 2 | 1 | 84080 |
| 1 | 27 | 2 | 3 | 1 | 74004 |
| 0 | 57 | 1 | 2 | 1 | 101962 |
| 0 | 70 | 3 | 2 | 1 | 91455 |
| 1 | 37 | 3 | 2 | 1 | 42190 |
| 0 | 26 | 2 | 2 | 1 | 76170 |
| 1 | 14 | 2 | 4 | 1 | 37820 |
| 0 | 22 | 1 | 2 | 1 | 58400 |
| 1 | 50 | 2 | 2 | 1 | 98200 |
| 0 | 38 | 2 | 3 | 1 | 74360 |
| 0 | 42 | 1 | 2 | 1 | 99120 |
| 1 | 41 | 4 | 2 | 1 | 54590 |
| 0 | 28 | 1 | 1 | 1 | 68200 |
| 1 | 27 | 1 | 4 | 1 | 67160 |
| 0 | 72 | 3 | 3 | 2 | 88455 |
| 0 | 38 | 2 | 2 | 2 | 68445 |
| 0 | 70 | 5 | 2 | 2 | 104980 |
| 0 | 70 | 2 | 1 | 2 | 94180 |
| 0 | 14 | 2 | 2 | 2 | 30400 |
| 0 | 14 | 1 | 2 | 2 | 54300 |
| 0 | 52 | 2 | 2 | 2 | 91200 |
| 0 | 182 | 10 | 2 | 2 | 259820 |
| 0 | 72 | 5 | 2 | 2 | 107785 |
| 0 | 214 | 6 | 2 | 2 | 275155 |
| 1 | 152 | 5 | 2 | 2 | 213200 |
| 1 | 32 | 2 | 2 | 2 | 75100 |
| 0 | 4 | 0.2 | 2 | 2 | 16964 |
| 1 | 58 | 4 | 1 | 2 | 93352 |
| 0 | 12 | 0.5 | 2 | 3 | 26034 |
| 1 | 17 | 2 | 2 | 3 | 67680 |
| 0 | 162 | 5 | 2 | 3 | 182455 |
| 0 | 66 | 5 | 2 | 3 | 68568 |
| 0 | 37 | 1 | 2 | 3 | 48640 |
| 0 | 35 | 1 | 2 | 3 | 45887 |
| 1 | 20 | 4 | 2 | 3 | 45540 |
| 0 | 152 | 8 | 2 | 3 | 104400 |
| 0 | 8 | 2 | 2 | 3 | 4640 |
| 0 | 32 | 1 | 2 | 3 | 46260 |
| 0 | 67 | 3 | 3 | 3 | 49320 |
| 1 | 17 | 2 | 2 | 3 | 57460 |
| 0 | 82 | 2 | 2 | 3 | 89550 |
| 0 | 77 | 4 | 2 | 3 | 86650 |
| 0 | 14 | 1 | 3 | 3 | 65610 |
| 0 | 70 | 3 | 3 | 4 | 99850 |
| 0 | 12 | 2 | 2 | 4 | 39560 |
| 0 | 50 | 3 | 2 | 4 | 98540 |
| 0 | 77 | 4 | 3 | 4 | 80400 |
| 1 | 12 | 1 | 2 | 4 | 37068 |
| 1 | 52 | 5 | 2 | 4 | 92000 |
| 0 | 42 | 1 | 3 | 4 | 116142 |
| 0 | 38 | 3 | 2 | 4 | 50800 |
| 0 | 62 | 5 | 2 | 4 | 65750 |
| 1 | 38 | 2 | 2 | 4 | 66860 |
| 0 | 104 | 3 | 3 | 4 | 114080 |
| 0 | 77 | 3 | 2 | 4 | 101400 |
| 1 | 26 | 0.5 | 3 | 4 | 63895 |
| 0 | 42 | 2 | 3 | 5 | 57275 |
| 0 | 77 | 3 | 2 | 5 | 92860 |
| 0 | 42 | 1 | 2 | 5 | 46200 |
| 0 | 45 | 5 | 2 | 5 | 58050 |
| 0 | 42 | 2 | 2 | 5 | 68900 |
| 0 | 14 | 0.5 | 2 | 5 | 23400 |
| 0 | 20 | 2 | 2 | 5 | 49170 |
| 0 | 67 | 2 | 5 | 5 | 69325 |
| 0 | 102 | 5 | 2 | 5 | 105400 |
| 1 | 30 | 4 | 2 | 5 | 68930 |
| 0 | 55 | 2 | 3 | 5 | 80200 |
| 0 | 102 | 5 | 2 | 5 | 68560 |
| 0 | 152 | 5 | 2 | 5 | 185460 |
| 0 | 37 | 3 | 4 | 5 | 60200 |
| 0 | 82 | 1 | 3 | 5 | 79528 |
| 0 | 50 | 2 | 2 | 5 | 51070 |
| 0 | 122 | 3 | 2 | 5 | 155028 |
| 0 | 212 | 6 | 4 | 5 | 186900 |
| 1 | 50 | 2 | 2 | 5 | 60160 |
| 0 | 12 | 5 | 2 | 5 | 36000 |
| 0 | 22 | 1 | 3 | 5 | 46825 |
| 0 | 27 | 1 | 4 | 5 | 45600 |
| 1 | 142 | 3 | 2 | 6 | 90400 |
| 0 | 27 | 2 | 1 | 6 | 49960 |
| 0 | 47 | 2 | 2 | 6 | 57270 |
| 0 | 77 | 3 | 2 | 6 | 96600 |
| 0 | 44 | 4 | 4 | 6 | 56950 |
Expert Answer:
