Lesson Plan for Markov Chain Monte Carlo (MCMC) with Julia

Monte Carlo Markov Chain (MCMC) algorithms are essential for sampling from probability distributions when direct sampling is challenging. Let's dive into implementing one of the most popular MCMC algorithms, the Metropolis-Hastings algorithm, in Julia.

This is a R Markdown ioslides presentation regarding Point Estimation and Confidence Intervals (CI), as well as using the 'mtcars' dataset as an example for those topics.

Thyroid Disease UCI Dataset, All about Health with Association Rules Mining