- Engineering & Materials
- Environmental engineering
- Applications of Bayes' theorem for predicting environmental damage
Applications of Bayes' theorem for predicting environmental damage
Gronewold, Andrew D. National Exposure Research Laboratory, U.S. Environmental Protection Agency Research Triangle Park, North Carolina.
Vallero, Daniel A. National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina.
- Bayesian statistics
- Bayes' theorem
- Applications of Bayes' theorem
- Links to Primary Literature
- Additional Readings
Ecosystems are inherently complex, and despite efforts to identify and model causal chains linking ecosystem disturbances with ecosystem response, there are inevitable discrepancies between observed and predicted conditions in the natural environment. Uncertainty, variability, and change all contribute to these differences, yet they are often ignored in predicting environmental problems. Statistical modeling techniques represent a general classification of tools that can help address discrepancies between predictions and observations, and Bayesian statistics in particular has recently been demonstrated to be a novel and effective tool for forecasting environmental pollutant problems because of its unique approach to quantifying uncertainty and variability.
The content above is only an excerpt.
for your institution. Subscribe
To learn more about subscribing to AccessScience, or to request a no-risk trial of this award-winning scientific reference for your institution, fill in your information and a member of our Sales Team will contact you as soon as possible.
to your librarian. Recommend
Let your librarian know about the award-winning gateway to the most trustworthy and accurate scientific information.
AccessScience provides the most accurate and trustworthy scientific information available.
Recognized as an award-winning gateway to scientific knowledge, AccessScience is an amazing online resource that contains high-quality reference material written specifically for students. Its dedicated editorial team is led by Sagan Award winner John Rennie. Contributors include more than 9000 highly qualified scientists and 42 Nobel Prize winners.
MORE THAN 8500 articles and Research Reviews covering all major scientific disciplines and encompassing the McGraw-Hill Encyclopedia of Science & Technology and McGraw-Hill Yearbook of Science & Technology
115,000-PLUS definitions from the McGraw-Hill Dictionary of Scientific and Technical Terms
3000 biographies of notable scientific figures
MORE THAN 17,000 downloadable images and animations illustrating key topics
ENGAGING VIDEOS highlighting the life and work of award-winning scientists
SUGGESTIONS FOR FURTHER STUDY and additional readings to guide students to deeper understanding and research
LINKS TO CITABLE LITERATURE help students expand their knowledge using primary sources of information