Tutorial Notes for Bayesian Statistics
$$
\newcommand{\indep}{\mathrel{\perp\mkern-10mu\perp}}
\newcommand{\P}{\mathbb{P}}
\newcommand{\R}{\mathbb{R}}
\newcommand{\E}{\mathbb{E}}
\newcommand{\Var}{\operatorname{Var}}
\newcommand{\Cov}{\operatorname{Cov}}
\newcommand{\1}[1]{\mathbf{1}\\{#1\\}}
$$
Bayesian Inference
Posterior Distribution
The intuition behind the posterior distribution:
“It is a weighted version of likelihood! … just weighting the likelihood using my prior belief on theta …”
Useful Resource
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17. Bayesian Statistics MIT 18.650 Statistics for Applications, Fall 2016
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Statistical Rethinking (2022 Edition) github, this is a recommanded bayesian textbook with video lectures.