This introduction can be used, at the beginning graduate level, for a
one-semester course on probability theory or for self-direction without
benefit of a formal course; the measure theory needed is developed in
the text. It will also be useful for students and teachers in related
areas such as finance theory, electrical engineering, and operations
research. The text covers the essentials in a directed and lean way with
28 short chapters, and assumes only an undergraduate background in
mathematics. Readers are taken right up to a knowledge of the basics of
Martingale Theory, and the interested student will be ready to continue
with the study of more advanced topics, such as Brownian Motion and Ito
Calculus, or Statistical Inference.