International Society for Bayesian Analysis (ISBA

What is Bayesian Analysis?

Scientific inquiry is an iterative process of integrating and accumulating information. Investigators assess the current state of knowledge regarding the issue of interest, gather new data to address remaining questions, and then update and refine their understanding to incorporate both new and old data. Bayesian inference provides a logical, quantitative framework for this process. It has been applied in a multitude of scientific, technological, and policy settings.

"Bayesian" refers to the Reverend Thomas Bayes. The development of probability theory in the early 18th century arose to answer questions in gambling, and to underpin the new and related ideas of insurance. A problem arose, known as the question of inverse probability: the mathematicians of the time knew how to find the probability that, say, 4 people aged 50 die in a given year out of a sample of 60 if the probability of any one of them dying was known. But they did not know how to find the probability of one 50-year old dying based on the observation that 4 had died out of 60. The answer was found by Thomas Bayes, and was published in 1763 (the year after his death). Like many educated men of his time, Bayes was both a clergyman and an amateur scientist/mathematician. His solution, known as Bayes' theorem, underlies, and gave its name to, the modern Bayesian approach to the analysis of all kinds of data.

For more background on Bayesian methods, with thanks to Kate Cowles, Rob Kass, and Tony O'Hagan, click here. A brief explanation of the layout of this website is given in more detail here.