Bayesian Updating and Bayesian Statistics

In this podcast episode, the hosts discuss the concept of Bayesian updating and Bayesian statistics. Bayesian beliefs are described as beliefs in statistics that are expressed as probabilities. The hosts provide an example of asking about the location of keys, where the belief is 90% that they are by the door. They explain that Bayesian belief systems involve considering different hypotheses or prior beliefs, and when evidence is obtained that contradicts one hypothesis, the beliefs should be updated. They introduce Bayes' theorem as a way to update beliefs based on new evidence and explain how the likelihood of a theory producing evidence is calculated.