Stochastic Methods in Scientific Computing: From Foundations to Advanced Techniques (Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series)

The book “Stochastic Methods in Scientific Computing: From Foundations to Advanced Techniques” is aimed at teaching stochastic modeling. It starts with the basics and gradually shows the recent developments in the field. This resource provides theory and real-world applications for every scientist willing to have a well-balanced book.

"Stochastic Methods in Scientific Computing: From Foundations to Advanced Techniques" emphasizes practicality and relevance by explaining how stochastic methods are used across many disciplines, including Social Sciences, Particle Physics, Computer Science, Modern-day Machine Learning, and AI. Furthermore, it is accompanied by procedural examples presented in a way that makes numbers less frightening. It also specializes in techniques for solving complex problems of stochastic simulations that will benefit anyone within the realm of scientific computing worldwide.

Stochastic Methods in Scientific Computing: From Foundations to Advanced Techniques Table of Contents:

1. Random numbers and probability distribution

   1. Quantifying randomness
   2. Pseudo randomness
   3. Designing probability distributions
   4. Applications: Poisson and exponential distributions

2. Central limit theorem

   1. Conditions and theorem
   2. The normal distribution
   3. Independent measurements and error propagation

3. Beyond the normal distribution

   1. Cauchy-Lorentz distribution and the failure of error reduction
   2. Pareto distribution and applications

4. Exercises

Who is this course for?

1. Those who want scientific computing
2. People taking numerical method courses
3. Finance professionals, physicists, biologists, or what have you
4. Someone with an interest on the application of stochastic modeling

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