Module 18:
Simulation and Monte Carlo reasoning

Module 18

What this module is for

Both should understand simulation; QR learners should implement it. The central outcome is a justified numerical answer with uncertainty, not a histogram that looks plausible.

Lesson 18.1 · Core

Reproducible random experiments

Depth: Working proficiency

QT/QR relevance: Especially QR; trustworthy computational work

Lesson 18.2 · Core

Inverse transforms and distribution generators

Depth: Working proficiency

QT/QR relevance: Both; implementing probability models

Lesson 18.3 · Core

Acceptance–rejection sampling

Depth: Working proficiency

QT/QR relevance: Especially QR; non-standard distributions

Lesson 18.4 · Core · QR Extension

Simulating Gaussian vectors

Depth: Working proficiency; derivation at researcher depth

QT/QR relevance: QR; correlated scenarios

Lesson 18.5 · Core

Monte Carlo estimates and error bars

Depth: Working proficiency

QT/QR relevance: Both; interpreting numerical evidence

Lesson 18.6 · Research Depth

Variance reduction

Depth: Advanced / quant researcher depth — Extension

QT/QR relevance: QR; more efficient numerical experiments

Lesson 18.7 · Research Depth

Importance sampling

Depth: Advanced / quant researcher depth — Extension

QT/QR relevance: QR; rare-event estimation

Assessment

Module 18 assessment

Open assessment · No submitted assessment yet