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  2. Bayesian inference in marketing - Wikipedia

    en.wikipedia.org/wiki/Bayesian_inference_in...

    An example of the application of Bayesian decision theory for promotional purposes could be the use of a test sample in order to assess the effectiveness of a promotion prior to a full scale rollout. By combining prior subjective data about the occurrence of possible events with experimental empirical evidence gained through a test market, the ...

  3. Decision theory - Wikipedia

    en.wikipedia.org/wiki/Decision_theory

    The mythological Judgement of Paris required selecting from three incomparable alternatives (the goddesses shown).. Decision theory or the theory of rational choice is a branch of probability, economics, and analytic philosophy that uses the tools of expected utility and probability to model how individuals would behave rationally under uncertainty.

  4. Bayesian statistics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_statistics

    Bayesian statistics (/ ˈ b eɪ z i ə n / BAY-zee-ən or / ˈ b eɪ ʒ ən / BAY-zhən) [1] is a theory in the field of statistics based on the Bayesian interpretation of probability, where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous ...

  5. Bayesian inference - Wikipedia

    en.wikipedia.org/wiki/Bayesian_inference

    Bayesian inference (/ ˈ b eɪ z i ə n / BAY-zee-ən or / ˈ b eɪ ʒ ən / BAY-zhən) [1] is a method of statistical inference in which Bayes' theorem is used to calculate a probability of a hypothesis, given prior evidence, and update it as more information becomes available.

  6. Bayesian econometrics - Wikipedia

    en.wikipedia.org/wiki/Bayesian_econometrics

    Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation of probability , as opposed to a relative-frequency interpretation.

  7. Bayes estimator - Wikipedia

    en.wikipedia.org/wiki/Bayes_estimator

    In estimation theory and decision theory, a Bayes estimator or a Bayes action is an estimator or decision rule that minimizes the posterior expected value of a loss function (i.e., the posterior expected loss). Equivalently, it maximizes the posterior expectation of a utility function.

  8. Howard Raiffa - Wikipedia

    en.wikipedia.org/wiki/Howard_Raiffa

    His book Applied Statistical Decision Theory with Robert Schlaifer introduced the idea of conjugate prior distributions.; A lecture of his in the 1960s concerning the use of Bayesian methods for betting on horses gave John Craven USN, a US Navy scientist the idea of using Bayesian methods to search for a missing US Air Force hydrogen bomb lost near Palomares, Spain in the 1966 Palomares B-52 ...

  9. Coherence (statistics) - Wikipedia

    en.wikipedia.org/wiki/Coherence_(statistics)

    The coherency principle in Bayesian decision theory is the assumption that subjective probabilities follow the ordinary rules/axioms of probability calculations (where the validity of these rules corresponds to the self-consistency just referred to) and thus that consistent decisions can be obtained from these probabilities. [1]