When assessing a chemical compound for possible regulation,
should toxicity be assumed? Or should it be considered safe,
until proven otherwise? And are these the only choices?
Classical statistical inference sets up artificial “hypotheses”
to test, but the answers often do not contribute much to the
decision-making process. Bayesian methods, by contrast, are
aimed at optimizing decisions, in light of costs and benefits.
This newer approach is covered in Paul Black’s online course:
“Bayesian Environmental Statistics” (Mar. 25 – Apr. 22).
A few of the upcoming statistics.com courses:
Feb 25: Environmental Sampling
Feb 25: Introduction to Bayesian Statistics
Mar 25: Bayesian Environmental Statistics (more below)
Apr 29: Bayesian Regression Modeling via MCMC Techniques
In “Bayesian Environmental Statistics,” participants will learn
to incorporate knowledge or estimates of the "state of the world,"
as well as the costs and benefits of alternative actions
(or inaction), via the application of Bayesian statistical
methods to environmental data and decision-making.
Paul Black is a consultant with Neptune and Co. in Los Alamos,
New Mexico. He has clients in both the private sector and in
government, including regulatory agencies such as the US
Environmental Protection Agency. His expertise includes the
application of Bayesian statistical methods to environmental
data and decision-making problems. Participants can ask
questions and exchange comments with Dr. Black via a private
discussion board throughout the period of the course.
The course takes place online at statistics.com in a series of 4
weekly lessons and assignments. Participate at your own convenience;
there are no set times when you are required to be online.
You may leave the list at any time by sending the command
to [log in to unmask], leaving the subject line blank.