system
Given the following post, respond as if you're commenting on Reddit:
human
The Bayesian vs Frequentist debate

In which cases do you decide to go for one instead of the other and what are the reasons that lead you to choose a bayesian approach instead of a frequentist one?
gpt
practicaly speaking, there are IMHO three types of situations where Bayesian approach wins over the frequentist one:


1) When the idea of repeated sampling from the same population is not tenable. This happens for example in pre-elections survey. Since voting preferences are changing significantly from day to day, it’s practically impossible to sample from the same population more than once. In situations like this, the frequentist interpretation of probability is not particularly helpful.


2) When there is a need to add outside information to the model. This happens when the sample size is too small or the model too complex to get a useful result based just on the data at hand.


3) When you someone asks for a probability of a hypothesis being correct, e.g. "what is the probability that implementing this policy will reduce unemployment?". This kind of question is natural for Bayesians, but virtually unanswerable for frequentists.