A Statistical Approach to Analyzing Engineering Estimates and Bids

Roshanak Farshidpour, Kiana Negoro and Fariborz M. Tehrani
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Roshanak Farshidpour: Department of Civil and Environmental Engineering, Samueli School of Engineering, University of California, Los Angeles, CA 90095, USA
Kiana Negoro: Department of Civil and Geomatics Engineering, Lyles College of Engineering, California State University, Fresno, CA 93740, USA
Fariborz M. Tehrani: Department of Civil and Geomatics Engineering, Lyles College of Engineering, California State University, Fresno, CA 93740, USA

Stats, 2021, vol. 4, issue 1, 1-9

Abstract: This paper introduces a methodology to assess the accuracy of engineering estimates in relation to the final project cost. The objective of this assessment is to develop a comprehensive approach towards obtaining a more reliable estimate of the project cost. This approach relies on the review of a synthesis of literature, which provides a basis for determining key components in the estimation of the capital cost of a project. A systematic review of existing data for selected projects was obtained as well. Employed data cover sampled public transportation projects to maintain existing infrastructure within selected geographical location and specified time. Enhanced analysis of existing data through statistical models was employed to indicate potential measures for prevention of errors in the estimate due to uncertainties in the time, cost, and method of construction. The comparison of results with similar findings from past research shows the effectiveness of presented methodologies and opportunities to enhance statistical analyses of bids and engineering estimates. Conclusions enable project managers to address uncertainties in the bidding process and enhance financial sustainability of projects within specific programs.

Keywords: bids; construction costs; estimates; procurement; quantitative analysis (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2021
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