Stochastic Processes (Classics in Applied Mathematics, Series Number 24)

The math which goes into stochastic theory is key and fundamental; this book is a very readable introduction to the material. Where most books just have the equations (and typically in the tersest form possible), this book makes an effort to explain what is going on "in words" and through some examples. If you are in a class or working with material where a firm understanding of stochastic theory is necessary, this is a good book to help you get up to speed. This is definitely not an advanced-level book or completely up-to-date, but the basics haven't changed. If you can find it used, it is cheap, too. This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions. Stochastic Processes is ideal for a course aiming to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models. It introduces the methods of probability model building and provides the reader with mathematically sound techniques as well as the ability to further study the theory of stochastic processes. Originally published in 1962, this was the first comprehensive survey of stochastic processes requiring only a minimal background in introductory probability theory and mathematical analysis. Stochastic Processes continues to be unique, with many topics and examples still not discussed in other textbooks.