Certificate in Bayesian Statistics and R
-- ViewingNowThe Certificate in Bayesian Statistics and R is a comprehensive course designed to equip learners with the essential skills required in today's data-driven world. This course emphasizes the importance of Bayesian statistics, a powerful approach to data analysis that enables learners to update their beliefs in light of new data.
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โข Introduction to Bayesian Statistics – Basic concepts, difference between Bayesian and frequentist statistics, probability theory.
โข Probability Distributions – Discrete and continuous distributions, probability density functions, cumulative distribution functions.
โข Bayes' Theorem – Derivation, conditional probability, prior and posterior distributions.
โข Conjugate Priors – Definition, types, selecting conjugate priors, examples.
โข MCMC (Markov Chain Monte Carlo) Methods – Overview, Metropolis-Hastings algorithm, Gibbs sampling.
โข Gelman-Rubin Diagnostic – Convergence assessment in MCMC, potential scale reduction factor.
โข Bayesian Inference – Point estimation, credible intervals, hypothesis testing.
โข R Programming – Data structures, data manipulation, basic functions and libraries.
โข R for Bayesian Analysis – Implementing Bayesian methods using R, rjags, rstanarm packages.
โข Case Studies – Real-world examples, applying Bayesian methods with R, interpreting results.
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