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.