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Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills

Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills

Roy L. Nersesian, Kenneth David Strang
Copyright: © 2013 |Volume: 2 |Issue: 4 |Pages: 18
ISSN: 2160-9624|EISSN: 2160-9632|EISBN13: 9781466634985|DOI: 10.4018/ijrcm.2013100105
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MLA

Nersesian, Roy L., and Kenneth David Strang. "Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills." IJRCM vol.2, no.4 2013: pp.61-78. http://doi.org/10.4018/ijrcm.2013100105

APA

Nersesian, R. L. & Strang, K. D. (2013). Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills. International Journal of Risk and Contingency Management (IJRCM), 2(4), 61-78. http://doi.org/10.4018/ijrcm.2013100105

Chicago

Nersesian, Roy L., and Kenneth David Strang. "Risk Planning with Discrete Distribution Analysis Applied to Petroleum Spills," International Journal of Risk and Contingency Management (IJRCM) 2, no.4: 61-78. http://doi.org/10.4018/ijrcm.2013100105

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Abstract

This study discussed the theoretical literature related to developing and probability distributions for estimating uncertainty. A theoretically selected ten-year empirical sample was collected and evaluated for the Albany NY area (N=942). A discrete probability distribution model was developed and applied for part of the sample, to illustrate the likelihood of petroleum spills by industry and day of week. The benefit of this paper for the community of practice was to demonstrate how to select, develop, test and apply a probability distribution to analyze the patterns in disaster events, using inferential parametric and nonparametric statistical techniques. The method, not the model, was intended to be generalized to other researchers and populations. An interesting side benefit from this study was that it revealed significant findings about where and when most of the human-attributed petroleum leaks had occurred in the Albany NY area over the last ten years (ending in 2013). The researchers demonstrated how to develop and apply distribution models in low cost spreadsheet software (Excel).

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