Question

1a)State two advantages of Bayesian data analysis over a classical approach?

1b)Explain why one would need a sensitivity analysis on the choice of prior distribution ?.

Answer 1

BAYESIAN DATA ANALYSIS OVER A CLASSICAL APPROACH:-

BAYESIN DATA ANALYSIS:-

The Bayesian methodology gives the

probability of fusing extra data that is outside to the example by earlier dispersions [8, 15]. This extra data may enhance precision and validity of estimations. The trustworthy districts consolidate this earlier data, while frequentist certainty interims depend just on the example information.

ADVANTAGES:-

Also, the understanding of traditional certainty interim might be on occasion silly; for instance when just a single example exists and extra examples can't be accumulated. At that point it is Bayesian methodology that gives a sensible understanding and traditional certainty interim ought not be connected.

PRIOR DISTRIBUTION:-

The earlier conveyance is a key piece of Bayesian induction (see Bayesian strategies and displaying) and speaks to the data around a questionable parameter that is joined with the likelihood appropriation of new information to yield the back appropriation, which thus is utilized for future deductions and choices including . The presence of an earlier dispersion for any issue can be advocated by adages of choice hypothesis; here we center around how to set up an earlier conveyance for some random application. As a rule, can and will be a vector, yet for effortlessness we will center here on earlier conveyances for parameters each one in turn.

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