Bayesian vs. Frequentist approach to define probabilities

What's the difference?

Consider event A = “dice shows 2”

Frequentist definition of probability

  • probability of event A is the relative frequency of this event “in the long run” –> P(A) = 1/6

Bayesian definition of probability

  • includes expert knowledge as well as experimental data to compute probabilities
  • the expert knowledge is represented by some (subjective) prior probability distribution
  • the data is incorporated in a likelihood function
  • the product of the prior and the likelihood, normalized, results in a posterior probability distribution that incorporates all the information known to date

Video explaining the difference between the two schools

 
public/bayesian_vs._frequentist_approach_to_define_probabilities.txt · Last modified: 2014/01/02 15:06 (external edit) · []
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