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What is Bayesian Inference & MCMC Techniques about?

This document discusses Bayesian inference and Markov chain Monte Carlo (MCMC) simulation. It introduces the Bayesian approach to statistical analysis using observational data and prior judgment. It provides an example of how Bayesian inference can be used to update a prior distribution based on new evidence. It then discusses MCMC simulation techniques like Markov chains and the Metropolis-Hastings algorithm that can be used to sample from posterior distributions when direct calculation is intractable. The

Author

Kanta Prajapat

Language

EN