A Comprehensive Guide to Bayesian Statistics
Bayesian Inference, Prior & Posterior Distn, Bayesian Interval Estimation, Bayesian Hypothesis Testing & Decision Theory
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3 hours
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Nov 2020
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$39.99
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What you will learn
An Overview on Statistical Inference
Frequentist vs Bayesian approach to Statistical Inference
Clearly understand Bayes Theorem and its application in Bayesian Statistics
Build a good intuitive understanding of Bayesian Statistics with real life illustrations
Master the key concepts of Prior and Posterior Distribution
Solve exam style numerical problems of computing Posterior Distribution for Population Parameter with different types of Prior
Understand Conjugate Prior and Jeffrey's Prior
Interval Estimation in Bayesian Statistics : Credible Intervals
Distinguish and work with Confidence Intervals and Credible Intervals
Solve problems of computing Credible Interval for Posterior Mean
Bayesian Hypothesis Testing: Bayes Factor
Learn to Interpret Bayes Factor
Solve numerical problems of computing Bayes Factor for two competing hypotheses
Build a solid understanding on Bayesian Decision Theory with examples
Decision Theory Terminology: State/Parameter Space, Decision Rule, Action Space, Loss Function
Minimizing Expected Loss
Real Life Illustrations of Bayesian Decision Theory
Use different Loss Functions: Squared Error Loss, Absolute Error Loss, 0-1 Loss
Decision Making with Frequentist vs Bayesian
Understand Bayesian Expected Loss, Frequentist Risk, and Bayes Risk
Admissibility of Decision Rules
Procedures to find Bayes Estimate & Bayes Risk: Normal & Extensive Form of Analysis
Solve numerical problems of computing Bayes Estimate and Bayes Risk for different Loss Functions
Bayesian's Defense & Critique
Applications of Bayesian Inference in various fields
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2824221
udemy ID
2/19/2020
course created date
12/15/2020
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