Although natural gas is currently inexpensive and nuclear power currently (and perhaps deservedly) does not have a good reputation, it is possible that more nuclear power plants will be constructed in the future. Table 4 presents data concerning the construction costs of light water reactor (LWR) nuclear power plants. The dependent variable, C, construction cost, is expressed in millions of dollars, adjusted to a 1976 base. Preliminary analysis of the data and economic theory indicate that variation in cost increases as cost increases. This suggests transforming cost by taking its natural logarithm. S Power plant capacity in MWe N Cumulative number of power plants built by the contractor Build a multiple regression model to predict ln(C) by taking S and N or their natural logarithms as the independent variables. Make sure to check for multicollinearity. Use residual analysis and R2 to check your model. State which variables are important in predicting the cost of constructing an LWR plant, and State a prediction equation that can be used to predict ln(C).
Although natural gas is currently inexpensive and nuclear power currently (and perhaps deservedly) does not have a good reputation, it is possible that more nuclear power plants will be constructed in the future. Table 4 presents data concerning the construction costs of light water reactor (LWR) nuclear power plants. The dependent variable, C, construction cost, is expressed in millions of dollars, adjusted to a 1976 base. Preliminary analysis of the data and economic theory indicate that variation in cost increases as cost increases. This suggests transforming cost by taking its natural logarithm. S Power plant capacity in MWe N Cumulative number of power plants built by the contractor Build a multiple regression model to predict ln(C) by taking S and N or their natural logarithms as the independent variables. Make sure to check for multicollinearity. Use residual analysis and R2 to check your model. State which variables are important in predicting the cost of constructing an LWR plant, and State a prediction equation that can be used to predict ln(C).
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 34PPS
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Question
Although natural gas is currently inexpensive and nuclear power currently (and perhaps deservedly) does not have a good reputation, it is possible that more nuclear power plants will be constructed in the future. Table 4 presents data concerning the construction costs of light water reactor (LWR) nuclear power plants. The dependent variable, C, construction cost, is expressed in millions of dollars, adjusted to a 1976 base. Preliminary analysis of the data and economic theory indicate that variation in cost increases as cost increases. This suggests transforming cost by taking its natural logarithm.
S Power plant capacity in MWe
N Cumulative number of power plants built by the contractor
- Build a multiple regression model to predict ln(C) by taking S and N or their natural logarithms as the independent variables. Make sure to check for multicollinearity. Use residual analysis and R2 to check your model.
- State which variables are important in predicting the cost of constructing an LWR plant, and
- State a prediction equation that can be used to predict ln(C).
Transcribed Image Text:Plant
C
N
1
460.05
687
14
2
452.99
1,065
1
3
443.22
1,065
1
4
652.32
1,065
12
5
642.23
1,065
12
345.39
514
7
272.37
822
8
317.21
457
1
457.12
822
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.
17
712.27
845
17
18
289.66
530
19
881.24
1,090
1
20
490.88
1,050
8
Transcribed Image Text:567.79
913
15
22
665.99
828
20
23
621.45
786
18
24
608.8
821
3
25
473.64
538
19
26
697.14
1,130
21
27
207.51
745
8
28
288.48
821
7
29
284.88
886
11
30
280.36
886
11
217.38
745
8
32
270.71
886
11
21
31
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