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- W4283169441 abstract "This chapter demonstrates how to apply a novel Bayesian auditing statistical technique with a predictive probability distribution model to predict petroleum accidents. The goal was to first develop the petroleum oil spill patterns for a given population, develop a predictive distribution model, and validate that using Bayesian audit statistical techniques. Sample data were taken from a U.S.-based state and fixed interval random sampling was used to select the records for the audit. A beta distribution was generated illustrating the materiality parameters along with the misstatement results." @default.
- W4283169441 created "2022-06-21" @default.
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- W4283169441 date "2022-06-24" @default.
- W4283169441 modified "2023-09-27" @default.
- W4283169441 title "Petroleum Industry Contingency Planning Using Auditing Theories and Inferential Statistics" @default.
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- W4283169441 doi "https://doi.org/10.4018/978-1-6684-5279-0.ch002" @default.
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