Bayesian Inference Quiz

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Questions and Answers

What is the initial prior distribution over θ denoted as?

  • p(α | θ)
  • p(θ | α) (correct)
  • p(θ)
  • p(α)

What is the probability of observing evidence E given hypothesis H?

  • P(E)
  • P(H)
  • P(E|H) (correct)
  • P(H|E)

What is the term used for the probability of a hypothesis given the observed evidence?

  • Posterior probability (correct)
  • Model evidence
  • Marginal likelihood
  • Prior probability

Which factor is the same for all possible hypotheses being considered?

<p>P(H) (A)</p> Signup and view all the answers

What is the posterior probability of a hypothesis proportional to?

<p>The prior probability and the likelihood (B)</p> Signup and view all the answers

Bayesian inference is a method of statistical inference that uses Bayes' theorem to update the probability for a hypothesis as more evidence becomes available.

<p>Bayesian inference is a method of mathematical inference that uses Bayes' theorem to update the probability for a hypothesis as more evidence becomes available. (A)</p> Signup and view all the answers

What is the posterior probability?

<p>The probability of a hypothesis after new evidence is observed. (B)</p> Signup and view all the answers

What does the prior probability represent in Bayesian inference?

<p>The probability of a hypothesis before new evidence is observed. (C)</p> Signup and view all the answers

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Study Notes

Bayesian Inference Basics

  • The initial prior distribution over θ is denoted as P(θ).
  • The probability of observing evidence E given hypothesis H is denoted as P(E|H).
  • The term used for the probability of a hypothesis given the observed evidence is posterior probability.
  • The likelihood P(E|H) is the same for all possible hypotheses being considered.
  • The posterior probability of a hypothesis is proportional to the product of the prior probability and likelihood.

Bayesian Inference Concepts

  • Bayesian inference is a method of statistical inference that uses Bayes' theorem to update the probability for a hypothesis as more evidence becomes available.
  • The posterior probability represents the updated probability of a hypothesis given the observed evidence.
  • The prior probability represents the probability of a hypothesis before observing the evidence.

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