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About this Course This Course is intended for all learners seeking to develop proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and much more. Through four complete courses (From Concept to Data Analysis; Techniques and Models; Mixture Models; Time Series Analysis) and a culminating project, you will cover Bayesian methods — such as conjugate models, MCMC, mixture models, and dynamic linear modeling — which will provide you with the skills necessary to perform analysis, engage in forecasting, and create statistical models using real-world data. ⭐⭐⭐⭐🕑TIME STAMP📋⭐⭐⭐⭐⭐ Bayesian Statistics: From Concept to Data Analysis 0:00:00 Module overview 0:04:15 Probability 0:14:09 Bayes theorem 0:24:55 Review of distributions 0:38:20 Frequentist inference 1:14:14 Bayesian inference 1:37:25 Priors 1:50:33 Bernoulli binomial data 2:35:13 Poisson data 2:43:40 Exponential data 2:47:43 Normal data 2:54:42 Alternative priors 3:06:16 Linear regression 3:51:15 Course conclusion Bayesian Statistics: Techniques and Models 3:52:16 Module overview 3:58:02 Statistical modeling 4:14:28 Bayesian modeling 4:46:50 Monte carlo estimation 5:31:15 Metropolis hastings 6:21:52 Jags 6:38:05 Gibbs sampling 7:14:06 Assessing convergence 7:40:06 Linear regression 8:41:43 Anova 9:11:16 Logistic regression 9:51:01 Poisson regression 10:23:29 Hierarchical modeling 11:23:21 Mixture models ♥️♥️Thanks for watching don't forget to like and Subscribe♥️♥️ ✨✨PLEASE IGNORE THESE TAGS✨✨ Bayesian, bayesian statistics, bayesian statistics online course, bayesian statistics online, bayesian statistics youtube