WasteTec is a large construction company that specializes in the construction of large wastewater treatment plants and recycling plants. A major cost driver in either type of facility is the capacity of the plant. For example, the capacity of a recycling plant is measured by the number of tons of water per day (TPD) that the plant can process. These plants can vary in size from a few hundred TPD to as many as several thousand TPD. Regression analysis is a useful method to estimate the cost of a new plant by using a regression equation developed from prior plant construction projects. The dependent variable of the regression is the actual construction cost of each project, while the independent variable is the TPD for the plant. Below is a sample of some recent projects and the related construction costs (in thousands).

		TPD		Cost
Location
Commerce, CA		360		$59,369
Hudson Fall, NY		400		$77,013
Layton, UT		420		$50,405
Oxford Township, NJ		450		$75,779
Savannah, GA		500		$87,439
Poughkeepsie, NY		506		$57,463
Panama City, FL		510		$60,730
Ronkonkoma, NY		518		$84,457
Okahuma,FL		528		$88,119
Spokane, WA		800		$152,902
Arlington, VA		975		$127,021
Camden, NJ		1,050		$163,395
York, PA		1,344		$139,302
Bridgeport, CT		2,250		$344,852
Chester, PA		2,688		$448,073

Required
1. Develop a regression model using Excel or an equivalent system to predict the cost of a proposed new plant in Babylon, New York, which will have a required capacity of 750 TPD. What is the predicted cost for the Babylon plant, using your regression?
2. Evaluate the precision and reliability of the regression you have developed. How could it beimproved?

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2.The regression has strong statistical measures. The R-squared is relatively high at 95.35%; the t-value for the independent variable TPD is high and the risk level (p) is low; the standard error of the estimate, at 25,458, is relatively small given the amounts predicted for the dependent variable, so overall, the regression looks very strong, and the management accountant should feel comfortable to rely on it in cost estimation. One way it would be improved is to significanly increase the amount of data; the current analysis is based on only 15 plants, and the accuracy of the regression model would improve with a much larger number of data points. Also, it is likely, that since the costs will increase faster for a project than the capacity (TPD) increase, due to engineering and other construction limitations, the analyst should ensure that the data under analysis is reasonably linear. If there is evidence of a non linear relationship between cost and TPD, then the analyst should use non-linear regression methods. There are a variety of non-linear regression approaches. A practical and simple to apply method is to convert the data by taking the natural log (ln) of each data point and then running the regression with the logged data. The conversion of logs removes the multiplicative type of non-linearity from the equation. To see this, review the discussion in footnote 13 in Appendix A. Source: Richard K Ellsworth, "Cost-to-Capacity Analysis for Estimating Project Costs," Construction Accounting and Taxation, September/October 2005, pp 5-10