The correct answer is False. Bayesian inference uses a subjective interpretation of probabilities, while frequentist inference uses a frequency interpretation of probabilities.
In Bayesian inference, probabilities are interpreted as degrees of belief. The probability of an event is the degree to which you believe that the event will occur. This interpretation of probability is subjective, because it depends on your own beliefs and knowledge.
In frequentist inference, probabilities are interpreted as long-run relative frequencies. The probability of an event is the proportion of times that the event would occur in a large number of repeated experiments. This interpretation of probability is objective, because it does not depend on your own beliefs or knowledge.
Bayesian inference is often used in situations where there is uncertainty about the true state of the world. For example, you might use Bayesian inference to estimate the probability of a disease in a patient, or to predict the outcome of an election.
Frequentist inference is often used in situations where there is a need to make decisions based on data. For example, you might use frequentist inference to test a new drug, or to set a safety standard.
In conclusion, Bayesian inference uses a subjective interpretation of probabilities, while frequentist inference uses a frequency interpretation of probabilities.