Measure Theory by Donald Cohn | Amazon Link

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Discussion Overview

The discussion centers around the book "Measure Theory" by Donald Cohn, focusing on its content, structure, and usefulness for learning measure theory and related topics. Participants share their experiences with the book and suggest alternatives for studying measure theory and real analysis.

Discussion Character

  • Exploratory, Technical explanation, Conceptual clarification

Main Points Raised

  • One participant notes that the second edition of Cohn's book has a more friendly format and includes a new chapter on probability.
  • Another participant mentions a perceived gap in proofs, specifically regarding the approximation-by-simple-functions proposition, attributing this to the delayed introduction of the general definition of measurability in Cohn's text.
  • A participant suggests alternative real analysis texts by Rudin and Folland for those open to studying other materials.
  • Another contributor expresses satisfaction with Cohn's second edition, highlighting its effectiveness for both learning and reference, and mentions the inclusion of a proof of the Banach-Tarski paradox in the appendix.

Areas of Agreement / Disagreement

Participants generally agree on the value of Cohn's book for learning measure theory, but there are differing opinions regarding its completeness and the adequacy of proofs provided.

Contextual Notes

Some participants express concerns about specific proofs and the timing of definitions, which may affect the understanding of certain concepts.

Who May Find This Useful

Readers interested in measure theory, real analysis, and probability theory may find this discussion helpful in evaluating Cohn's book and considering alternative resources.

For those who have used this book

  • Lightly Recommend

    Votes: 0 0.0%
  • Lightly don't Recommend

    Votes: 0 0.0%
  • Strongly don't Recommend

    Votes: 0 0.0%

  • Total voters
    3
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This is the book I used to learn measure theory. There is now a second edition featuring a slightly more friendly format, and a whole new chapter on probability.
I don't remember any lacking proofs with one exception - the approximation-by-simple-functions proposition. I guess this is because Cohn somewhat delays the introduction of the general definition of measurability. Rudin gives a concise (and unusually clear) proof in Real and Complex Analysis, Thm 1.17.
 
This is also where I learned measure theory from (2nd edition). I found this text great for both learning and as a reference. I haven't used any other measure theory textbooks, but I didn't feel the need to with this book handy. There is a nice chapter on probability theory, and a proof of the Banach-Tarski paradox in the appendix.
 

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