Reliability Goodness of Fit for Oil Spills in the Gulf of Mexico

Eschenbach and Harper (2006) analyzed offshore oil spills in the Gulf of Mexico with extensions to the northern seas of Alaska. This involved multiple methods including assessing what statistical distribution adequately fits the data. Empirical distribution function (EDF) statistical procedures are powerful goodness of fit tests and also provide for good visual assessments. The most powerful of the current EDF methods is the Anderson-Darling test. This paper focuses on the Anderson-Darling EDF goodness of fit procedure for both the two and three parameter Weibull distribution that is often used in reliability analysis. Excel VBA code has been developed to compute this test statistic and also the associated p-values to allow statistical significance tests. The Excel routines are available free at http://faculty.otterbein.edu/WHarper/. The functions are illustrated with Gulf of Mexico oil spill data

Reliability Confidence Intervals for Oil Spills in the Gulf of Mexico

An extensive study [Eschenbach and Harper (2006)] of offshore oil spills in the Gulf of Mexico with extensions to the northern seas of Alaska involved the estimation of the likelihood of oil spill volumes in the Gulf of Mexico for both pipeline and platform spills. This paper develops both maximum likelihood based reliability and percentile confidence intervals for the 3- parameter Weibull distribution. The statistical aspects are discussed along with applications of developed Excel VBA functions. The Excel routines are available free on the web at http://faculty.otterbein.edu/WHarper/. The functions are illustrated with Gulf of Mexico oil spill data

Maximum Likelihood Estimation Methodology Comparison for the Three-Parameter Weibull Distribution with Applications to Offshore Oil Spills in the Gulf of Mexico

Maximum Likelihood estimation of the two-parameter Weibull distribution is straightforward; however, there are multiple methods for maximum likelihood estimation of the three-parameter Weibull. This paper presents an evaluation of these methods using four data sets including oil spill data from the Gulf of Mexico. Highlighted are fairly major differences in the estimated parameters between nine statistical packages. A VBA routine has been developed allowing practitioners to implement three-parameter Weibull maximum likelihood estimate within Excel. The code and support documentation are available free at http:faculty.otterbein.edu/WHarper

Engineering Economy Analysis

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Engineering Economic Analysis -12/E.

The twelfth edition of the market-leading Engineering Economic Analysis offers comprehensive coverage of financial and economic decision making for engineers, with an emphasis on problem solving, life-cycle costs, and the time value of money. The authors\u27 concise, accessible writing, practical emphasis, and contemporary examples linked to students\u27 everyday lives make this text the most popular among students. New to the Twelfth Edition * 500 new or revised problems--answers to most even problems now in Appendix E * Six new and nine updated chapter-opening vignettes provide extended real-world examples * Twenty new Excel tutorial videos added to the updated set of thirty-six from the eleventh edition * New visual "five-button solutions" help simplify the use of spreadsheets and calculators * A new Appendix 12A aggregates coverage of personal income taxes, which now includes time value of money problems.The twelfth edition of the market-leading Engineering Economic Analysis offers comprehensive coverage of financial and economic decision making for engineers, with an emphasis on problem solving, life-cycle costs, and the time value of money. The authors\u27 concise, accessible writing, practical emphasis, and contemporary examples linked to students\u27 everyday lives make this text the most popular among students. In addition, with its extensive support package and logical progression of topics, this is the easiest book to teach from