Measure, Integral and Probability is a gentle introduction that makes measure and integration theory accessible to the average third-year undergraduate student. The ideas are developed at an easy pace in a form that is suitable for self-study, with an emphasis on clear explanations and concrete examples rather than abstract theory.
For this second edition, the text has been thoroughly revised and expanded. New features
·a substantial new chapter, featuring a constructive proof of the Radon-Nikodym theorem, an analysis of the structure of Lebesgue-Stieltjes measures, the Hahn-Jordan decomposition, and a brief introduction to martingales ·key aspects of financial modelling, including the Black-Scholes formula, discussed briefly from a measure-theoretical perspective to help the reader understand the underlying mathematical framework.
In addition, further exercises and examples are provided to encourage the reader to become directly involved with the material.
A good introduction to the subject at the advanced undergraduate level. Topics are introduced in a concrete manner, followed by generalizations. The generalizations could be clearer and more complete and that is the only issue I have with the book.
I had the first edition. It had too few exercises and I had a hard time trying to grasp what a nonmeasurable set was. It's not a bad book but it didn't gel with me. I didn't feel comfortable with measure until I read Klambauer's book on real analysis.