{"id":6971,"date":"2026-08-10T09:39:16","date_gmt":"2026-08-10T09:39:16","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-introduction-to-bayesian-statistics-2020-8\/"},"modified":"2026-08-10T09:39:16","modified_gmt":"2026-08-10T09:39:16","slug":"udemy-introduction-to-bayesian-statistics-2020-8","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-introduction-to-bayesian-statistics-2020-8\/","title":{"rendered":"Udemy \u2013 Introduction to Bayesian Statistics 2020-8"},"content":{"rendered":"
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Descriptions<\/h2>\n

Introduction to Bayesian Statistics, Bayesian statistics is used in many different areas, from machine learning, to data analysis, to sports betting and more. It\u2019s even been used by bounty hunters to track down shipwrecks full of gold. This beginner\u2019s course introduces Bayesian statistics from scratch. It is appropriate both for those just beginning their adventures in Bayesian statistics as well as those with experience who want to understand it more deeply. We begin by figuring out what probability even means, in order to distinguish the Bayesian approach from the Frequentist approach. Next we look at conditional probability, and derive what we call the \u201cBaby Bayes\u2019 Theorem\u201d, and then apply this to a number of scenarios, including Venn diagram, tree diagram and normal distribution questions. We then derive Bayes\u2019 Theorem itself with the use of two very famous counter-intuitive examples. We then finish by looking at the puzzle that Thomas Bayes\u2019 posed more than 250 years ago, and see how Bayes\u2019 Theorem, along with a little calculus, can solve it for us.<\/p>\n

What you\u2019ll learn<\/h3>\n