Frequentist statistics interprets probabilities as frequency of a certain outcome among a large number of trials. (Actually the limit as the number of trials te

Frequentist statistics interprets probabilities as frequency of a certain outcome among a large number of trials. (Actually the limit as the number of trials tend to infinity). A Bayesian interpretation of probability is "degree of belief". What is the probability that tomorrow there will be rain ? Well, a priori I believe it is about 33%. However the sky is clouded today, which has 50% probability to cause rain the next day, etc. etc. So Bayes rule kicks in and I can make a decision whether or not to carry umbrella. For a frequentist, probability of a single event is meaningless: 33% of all days in the past have been rainy. 50% of all days following cloudy days have been rainy, etc. . . If there were a large number of parallel worlds, in x % of them there would be rain, etc. etc.