Abstract
This chapter begins with the basic concepts of probability and discusses on the various types of probability models. Discrete Probability model is the most simple and intuitive type that involves a discrete set of possible outcomes and no time-dynamic elements. Continuous probability model is based on random variables and is particularly convenient for representing random times. Partial differential equations are explained by focusing on the diffusion equation. A point source solution to this partial differential equation can be easily derived, using Fourier transforms, to arrive at the normal density. The section, Introduction to Statistics explains the basics of statistics and its relation with diffusion model. Diffusion is the spreading of particles due to small random movements and it has been explained with real-world applications.
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