Frequentist vs Bayesian View

Frequentist View

  • Defines probability of some event in terms of the relative frequency with which the event tends to occur

  • More widely used and usually involves simpler calculations

  • Frequentists think deductively: "If the true population looks like this, then my sample might look like this."

  • Terminology: p value, significant, null hypothesis, or confidence interval

  • Draw conclusions strictly from what’s in that set of given data

Bayesian View

  • Defines probability in more subjective terms — as a measure of the strength of your belief regarding the true situation

  • Requires powerful computers and sophisticated software

  • Bayesians think inductively: "My sample came out like this, so the true situation might be this."

  • Terminology: prior probability, noninformative priors, and credible intervals

  • Broader view of "usable information" which typically starts with some prior probabilities (based on previous experiments) and then blend in the results of the latest experiment to revise those probabilities


  • A population includes all of the elements from a set of data.

  • A sample consists one or more observations drawn from the population.

Link: - Dummies Series: TWO VIEWS OF PROBABILITY

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