Preface

This book is a comprehensive guide to understanding various computational statistical simulations using Python.

This book starts with the foundation required to understand various methods and techniques before delving into complex topics. Developers working with simulation models will be able to put their knowledge to work with this practical guide. The book takes a hands-on approach to implementation and associated methodologies that will have you up and running and productive in no time.

Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, you will begin by exploring the numerical simulation algorithms, including an overview of relevant applications. You’ll learn how to use Python to develop simulation models and understand how to use several Python packages. You will then explore various numerical simulation algorithms and concepts, such as a Markov Decision Process, Monte Carlo methods, and bootstrapping techniques.

By the end of this book, you will be able to construct simulation models.