Certificate in Bayesian Statistics for Healthcare
-- ViewingNowThe Certificate in Bayesian Statistics for Healthcare is a comprehensive course that equips learners with essential skills in Bayesian statistics, a crucial area of data analysis in healthcare. This course is important due to the increasing demand for healthcare professionals who can effectively interpret and analyze complex healthcare data using Bayesian methods.
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โข Introduction to Bayesian Statistics - Basic concepts, principles, and benefits of Bayesian statistics.
โข Probability Theory - A review of probability concepts, including conditional probability, joint probability, and marginal probability.
โข Bayes' Theorem - Derivation, explanation, and applications of Bayes' theorem.
โข Prior, Likelihood, and Posterior Distributions - Understanding and calculating prior, likelihood, and posterior distributions.
โข Bayesian Inference - Performing Bayesian inference, including calculating posterior probabilities and making predictions.
โข Markov Chain Monte Carlo (MCMC) - Introduction to MCMC methods, including Metropolis-Hastings and Gibbs sampling.
โข Bayesian Hierarchical Models - Concepts and applications of hierarchical modeling in Bayesian statistics.
โข Model Evaluation and Comparison - Techniques for evaluating and comparing Bayesian models, such as deviance information criterion (DIC) and leave-one-out cross-validation.
โข Bayesian Computing - Hands-on experience using Bayesian software, such as Stan and JAGS, for analysis and computation.
โข Applications in Healthcare - Real-world applications of Bayesian statistics in healthcare, including clinical trials, diagnostics, and medical decision making.
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