Introduction
What this guide covers
Rigorous theory, probabilistic foundations, convergence, variance reduction, MCMC, and advanced applications — with fully worked examples.
Overview
Topics covered
- Introduction
- Conceptual Foundations
- 1.1 History and Historical Context
- 1.2 The Central Idea: Expectation as Integral
- 1.3 Probabilistic Fundamentals: LGN and TLC
- Pseudorandom Number Generation
Related concepts
Main connections
Compatible notation
Mathematical sample in LaTeX
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I = \int_{\mathcal{X}} f(\mathbf{x})\, d\mu(\mathbf{x}) = \mathbb{E}_\mu[f(\mathbf{X})]