Bayesian statistics in environmental engineering planning

James D. Englehardt, Ted W. Simon

Research output: Contribution to journalArticlepeer-review


Today's environmental engineer faces many uncertainties in designing systems to address environmental concerns. Uncertainties arising from a lack of information may range from population forecasts of the projected benefits of technologies designed to reduce global warming impacts to remedial levels for hazardous waste posing the least amount of risk. Quantitative assessments of uncertainty and variability using such methods as Bayesian statistics are more convincing than those using rules of thumb and other, less-formal arguments. It can provide a rigorous assessment of risk based on the information available.

Original languageEnglish (US)
Pages (from-to)21-26
Number of pages6
JournalJournal of Management in Engineering
Issue number5
StatePublished - Sep 1 2000

ASJC Scopus subject areas

  • Industrial relations
  • Engineering(all)
  • Strategy and Management
  • Management Science and Operations Research


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