Bayesian Interpretation

The Bayesian interpretation views probability as a measure of your uncertain knowledge about a situation, rather than just frequency of events. It updates this probability as new evidence becomes available, using Bayes’ theorem. For example, if you think there’s a certain chance a medical test is positive given a disease, Bayesian analysis adjusts that belief when actual test results come in. This approach helps make more informed decisions by continually refining our understanding based on incoming data, allowing us to incorporate prior knowledge and new evidence in a meaningful way.