Decision-making and Uncertainty Quantification Briefly explain the “frequentist” and Bayesian statistical analysis frameworks. From a decision...

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Decision-making and Uncertainty Quantification Briefly explain the “frequentist” and Bayesian statistical analysis frameworks. From a decision...

Decision-making and Uncertainty Quantification

Briefly explain the “frequentist” and Bayesian statistical analysis frameworks. From a decision analysis perspective, which approach would you prefer to quantify uncertainty? Justify your answer.

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Answer 1

Answer #1

Frequenist framework draws on conclusions from samlle data which gets emphasized by frequency of data.

However Bayesian framework takes more of evidence and predetermined information from data to draw conclusions.

This helps higher accuracy prediction in Bayesian statistics as uncertainty mitigation is high as it takes evidence more into consideration and lowering risks and helps in taking calibrated view and decisions. Bayesian network also takes hypothesis testing and computes confidence intervals.

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Answer 2

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Decision-making and Uncertainty Quantification Briefly explain the “frequentist” and Bayesian statistical analysis frameworks. From a decision...

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Decision-making and Uncertainty Quantification Briefly explain the “frequentist” and Bayesian statistical analysis frameworks. From a decision...