Statistical Modeling & Regression · Bayesian Statistics

Advanced Bayesian Statistics · Inference and Modeling

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Chart from the original guide

Overview

Topics covered

  • Introduction
  • Bayesian Statistics
  • Epistemological and Axiomatic Foundations
  • Axiomatization of Coherent Probability (Cox and de Finetti)
  • De Finetti's Representation Theorem
  • The Bayesian Inference Paradigm

Related concepts

Main connections

  • Bayes' theorem & priors
  • Maximum likelihood estimation
  • Variance & standard deviation
  • Calculus & differentiation
  • Markov chain Monte Carlo (MCMC)
  • Hypothesis testing

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

P(x∧y∣z)=P(x∣y∧z)P(y∣z)
View LaTeX sourceP(x \wedge y \mid z) = P(x \mid y \wedge z) \, P(y \mid z)