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
1. 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.
2. Use residual analysis and R2 to check your model.
3. State which variables are important in predicting the cost of constructing an LWR plant, and
4. State a prediction equation that can be used to predict ln(C).
Data Concerning Construction of Light Water Reactors
(Please find table 4 in the attachment)
1. Need to have at least 1 peer-reviewed article as the reference and textbook as the reference
2. Need in-text citation
3. Please find the attachments as the power points of the course for reference.
4. Textbook Information:
Bowerman, B., Drougas, A. M., Duckworth, A. G., Hummel, R. M. Moniger, K. B., & Schur, P. J. (2019). Business statistics and analytics in practice (9th ed.). McGraw-Hill
5. Please find the Course Learning Outcome list of this course in the attachment
6. Please provide your work in detail and include in-text citations.
7. Please find Table 4 in the attachment
8. Please find the attached 2 excel files as the sample of the activity
9. Need to use data analysis method of “Regression” in the excel
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