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Programming & Scientific Computing · Python & Data Science

Probability, simulation, and sampling methods in Python · Academic chalkboard

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Computational Treatment of Uncertainty

Overview

Topics covered

Introduction
Python: Probability, Simulation and Sampling
Pseudorandom number generation and Python APIs
1.1 Evolution of Python APIs: from Mersenne Twister to PCG64
Discrete probability distributions
2.2 Treatment in SciPy: evaluation of the discrete probability space

Related concepts

Main connections

Compatible notation

Mathematical sample in LaTeX

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

X_{n+1} = (a \cdot X_n + c) \pmod{m}

View LaTeX source

X_{n+1} = (a \cdot X_n + c) \pmod{m}