1.Consider the data table 4. Augment the data by the dummy variable "cooling tower" as given in Table 6.

a.Build a multiple regression model to predict ln (C) by taking S and N or their natural logarithms, as well as CT, as the independent variables. Make sure to check for multicollinearity.

b.Use residual analysis and R² to check your model.

c.State which variables are important in predicting the cost of constructing an LWR plant.

d.State a prediction equation that can be used to predict ln(C).

e.Does adding CT improve R²? If so, by what amount?

Please provide your work in detail and include in-text citations.

Table 4 Table 6 Data Concerning Construction of Light Water Reactors Cooling Tower Data in Constructing Light Water Reactors Plant C S N Plant CT 460.05 687 14 1 0 2 452.99 1,065 3 443.22 1.065 1 1 4 652.32 1.065 12 5 642.23 1,065 12 1 6 345.39 514 3 272.37 822 5 8 317.21 457 9 457.12 822 5 10 690.19 792 2 11 350.63 560 3 12 402.59 790 6 13 412.18 530 2 14 495.58 1,050 7 15 394.36 850 16 16 423.32 778 3 16 17 712.27 845 17 -OO 18 289.66 530 2 18 19 881.24 1,090 19 20 490.88 1,050 8 20 0 21 567.79 913 15 21 22 665.99 828 20 22 0 23 621.45 786 18 23 1 24 608.8 321 3 24 0 25 473.64 538 19 25 26 697.14 1,130 21 26 27 207.51 745 8 27 0 28 288.48 321 7 28 29 284.88 886 11 29 30 280.36 886 11 30 31 217.38 745 8 31 0 32 270.71 886 11 32 1