Bayesian analysis is a probabilistic classification method based on Bayes' theorem (postulated by an English Mathematician named...

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Bayesian analysis is a probabilistic classification method based onBayes' theorem
(postulated by an English Mathematician named Thomas Bayes). Insummary, the
Bayesian theory rests on the belief that the evidence about thetrue state of a given
problemcan be expressed in term of the degree of understanding of theunderlying
issues.That degree of understanding can in turn be expressed in terms ofprobability.
Andbased on the observation, the theorem provides the relationshipbetween the
probabilities of two possible events and their conditionalprobabilities.
Theformula for Bayes Theorem is given as: P(A|B) = P(B|A) *P(A)/P(B)
Question:
Discussthe reasons for using Bayesian analysis when faced with uncertaintyin
makingdecisions.
Discussion Requirements:
Howwould you describe Bayesian Theorem?
Describe the assumptions of Bayesian analysis.
Providethe example of problem where one can use Bayesian analysis in BigData Analytics.
Describe the the problems with Bayesian analysis.

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In statistical inference there are two ways for interpretations of probability include Frequentist or Classical inference and Bayesian inference It usually is unlike each other in the classical nature of probability Classical inference defines probability as the limit of an events relative frequency for a large number of experiments and only in the sense of random experiments which are well defined Another side Bayesian inference can impose probabilities to each statement when a random process is not See Answer

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