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The Foundations of Statistics 2nd Revised ed. Edition

4.4 out of 5 stars 11 customer reviews
ISBN-13: 978-0486623498
ISBN-10: 0486623491
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Product Details

  • Paperback: 310 pages
  • Publisher: Dover Publications; 2nd Revised ed. edition (June 1, 1972)
  • Language: English
  • ISBN-10: 0486623491
  • ISBN-13: 978-0486623498
  • Product Dimensions: 5.4 x 0.7 x 8.5 inches
  • Shipping Weight: 10.4 ounces (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (11 customer reviews)
  • Amazon Best Sellers Rank: #408,344 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

Format: Paperback
Savage rigorously reworks the approach of Frank Plumpton Ramsey to give us a personalist (subjectivist) probability construct, and uses this to found a theory of statistics. Even many of us who disagree strongly with Savage are greatly impressed by this remarkable work.
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Format: Paperback Verified Purchase
One of the earliest books/texts to present the Bayesian paradigm. You need at least three semesters of calculus to do the math - Savage was one of the statisticians who worked on the Manhattan Project and this text is very rigorous.
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Format: Paperback Verified Purchase
Very foundational work on decision theory. Be prepared to have your noggin challenged! Make sure you brush up on boolean algebra and calculus. A fundamental understanding of probabilities is needed too.
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Format: Paperback Verified Purchase
I like this book because it addresses not only the usual "frequentist" approach taught in many undergraduate programs, but also includes "personal" aspects of statistics. This is not a "casual" reading text; it is fairly terse and requires some mathematical sophistication on the part of the reader
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Format: Paperback
This is not an easy book, but it is worth reading if you want to get a particular perspective on "the foundations of statistics".
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Format: Kindle Edition Verified Purchase
Amazing book. It teaches and describes a science (Savagean Statistics) through which one can address and solve numerical issues which basic statistics cannot, due to its several limitations.
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