Bayes vs. Frequentist debate

The Bayesian versus frequentist debate in statistics centers on how we interpret and update our knowledge about uncertainty. Frequentists rely on long-term data patterns and consider probability as the frequency of events in repeated trials. Bayesians, on the other hand, incorporate prior beliefs or existing knowledge and update these as new data become available, viewing probability as a degree of belief. Essentially, frequentists focus on objective data-driven methods, while Bayesians blend prior information with data to refine their understanding, offering more flexible and personalized insights.