Professional Certificate Bayesian Statistics R
-- ViewingNowThe Professional Certificate in Bayesian Statistics from <a href="https://www.edx.
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โข Introduction to Bayesian Statistics: Basic concepts, principles, and benefits of Bayesian statistics. Understanding probability, likelihood, and prior distributions.
โข Probability Distributions in R: Overview of probability distributions, focusing on discrete and continuous distributions in R. Generating random variables and visualizing distributions.
โข Bayes' Theorem in R: Implementing Bayes' theorem in R, deriving posterior distributions, and understanding the role of prior and likelihood.
โข Conjugate Priors in Bayesian Analysis: Introduction to conjugate priors, selecting appropriate conjugate priors in R, and demonstrating their benefits in Bayesian analysis.
โข MCMC & Gibbs Sampling: Overview of Markov Chain Monte Carlo (MCMC) and Gibbs sampling methods, implementing MCMC and Gibbs sampling in R, and understanding their role in Bayesian analysis.
โข Model Checking & Comparison: Evaluating and comparing Bayesian models in R, assessing model fit, and ensuring model assumptions are met.
โข Bayesian Hierarchical Modeling: Understanding the concept of hierarchical modeling, implementing hierarchical models in R, and interpreting posterior distributions.
โข Applications of Bayesian Statistics: Exploring real-world applications of Bayesian statistics in various fields, demonstrating how to apply Bayesian methods to solve complex problems using R.
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