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26 of 27 people found the following review helpful
4.0 out of 5 stars Especially good on Bayesianism and Frequentism
(FOUR AND A HALF STARS)
This is more an intro to the PHILOSOPHY of probability and inductive logic than an intro to the MATHEMATICS of probability of inductive logic, although some of the basic mathematical ideas are covered (which is useful if you're gonna discuss the philosophy). Do not get this book if you're just looking for a typical mathematical intro to...
Published on June 14, 2007 by Steve L

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17 of 28 people found the following review helpful
2.0 out of 5 stars Remedial reading
Like most scientists, I work with probabilities and statistics daily, but was looking for an nice introduction to the philosophy of probability to round out my interpretative knowledge. Unfortunately, this is more like a hand-holding high school introduction to the basic concepts of probability manipulations. I realize that it is "an introduction", so perhaps I should...
Published on July 1, 2012 by whiteelephant


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26 of 27 people found the following review helpful
4.0 out of 5 stars Especially good on Bayesianism and Frequentism, June 14, 2007
By 
Steve L (Los Angeles, CA) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
(FOUR AND A HALF STARS)
This is more an intro to the PHILOSOPHY of probability and inductive logic than an intro to the MATHEMATICS of probability of inductive logic, although some of the basic mathematical ideas are covered (which is useful if you're gonna discuss the philosophy). Do not get this book if you're just looking for a typical mathematical intro to statistics. But DO get this book if you want to know about the foundations of Bayesianism or are interested in the Frequentists vs. Bayesian debate. It is the best intro out there on the Frequentists/Bayesians issue, and it is extremely helpful for someone who is trying to get a handle on Bayesian reasoning. Also, those who are more into the mathematical aspects of probability could find this book useful in giving them a wider perspective on the subject. On the whole, it's clearly written and fun to read, although it is not an "easy" book. A basic knowledge of probability theory and some initial grasp of induction are good to have before reading this. But overall, it's highly recommended for those who want to know about the conceptual underpinnings of probability/induction in general, and Bayesian and Frequentism specifically.
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49 of 55 people found the following review helpful
4.0 out of 5 stars What do you mean, "probably"?, February 14, 2002
By 
Berel Dov Lerner (Western Galilee College, Israel) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
The best thing about this book is that it teachs basic probability theory while keeping the reader constantly aware of the on-going debate regarding what it means to talk in terms of probabilities, and of how that debate has shaped the development of probability theory. If you are a student taking a course in probability and statistics who would like to genuinely understand the conceptual basis of all those formulas they are teaching you, I suggest you read this book.
Some readers will be disappointed by this book. Since the book concentrates on the conceptual basis of probability and inductive logic, it does not give the reader enough technical tools to really do much applied mathematics. On the other hand, by the time Hacking gets around to discussing what students of philosophy will likely view as the big philosophical pay-off of probability theory (i.e. Bayesian and frequentist contributions to the problem of justifying induction) he devotes to them a mere 20 pages of not terribly deep discussion.
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37 of 42 people found the following review helpful
5.0 out of 5 stars For anyone, any thinker, June 6, 2002
By 
Steven Bucuvalas (Buffalo Creek, CO United States) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
I would HIGHLY recommend this book for anyone (including business men) who must make decisions with incomplete information and under uncertainty. Instead of focusing on the mechanics of statistics, it focuses on how to think about risky propositions.
I bought this book while working on a particular problem in machine learning, at a point where I had started realizing that I was losing clarity on my definition of probability. I was using the mechanics, but didn't clearly understand why the use was valid. This seemed an odd and embarrassing circumstance at the time, how could I not understand what "probability" means? As it turns out this confusion is one shared broadly in history of science, and in current applications of statistical mechanics.
Prof Hacking's writing is clear and entertaining, clearly aimed at engaging the reading audience.
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6 of 6 people found the following review helpful
5.0 out of 5 stars First Rate Introductory Text, January 30, 2009
By 
R. Albin (Ann Arbor, Michigan United States) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
This is a first rate introductory text prepared by a well known philosopher and expert on the logic and history of probability & statistics. The approach is disarmingly simple. Hacking avoids complicated math and proofs and teaches via the intuitive appeals to the underlying logic of these topics. Hacking begins with an intuitively based discussion of basic features of probability theory, expectation, Bayes rule, and decision analysis. This is followed by a particularly good exposition of the different senses of probability; belief-Bayesian and frequentist. Hacking shows how both approaches can be used fruitfully and rigorously in even mundane problems. These sections are followed by very nice chapters on the underlying logic of normal distributions, statistical hypothesis testing, and confidence intervals. This is the diametrical opposite of the cookbook approach used often in many statistics books and provides very nice understanding of key features of statistical methods. I never appreciated the strength of the confidence interval approach before reading this book. Hacking concludes with some concise but thoughtful chapters on the philosophical implications of these ideas, particularly as applied to the classic problem of induction. The quality of writing is excellent and the book features a large number of good examples and problems to work through. Strongly recommended to individuals who want to learn more about the basis of statistical methods.
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6 of 7 people found the following review helpful
5.0 out of 5 stars Best text on logic and philosophy of probability, June 20, 2009
This review is from: An Introduction to Probability and Inductive Logic (Paperback)
Maybe 1/3 of a college course in probability and statistics consists of a rapid trip, in math language, through basic conceptual ideas such as the interpretation of "probability", Bayes rule, significance tests and confidence intervals. This book, aimed at students of philosophy, treats this material and the associated math much more slowly and carefully -- relating probability to logic and philosophy, not just to math. For instance it has clear discussions of the principle of maximizing expected utility; the frequentist/Bayes philosophies and the coherence ideas emphasized by Bayesian apologists; the logic of significance tests and confidence intervals. Concepts are illustrated by creative selection of hypothetical story examples -- much more interesting than the usual math textbooks full of X's and Y's. The final 20 pages are a rather big jump toward technical philosophy -- arguing that both Bayesian and frequentist philosophies comprise "evasions" rather than "solutions" of "the problem of induction".

For a textbook, rather than bedtime reading, on this material it is hard to imagine a better treatment. My only criticism -- perhaps a criticism of analytic philosophy in general -- is that it seems more concerned with teaching the reader how to critique other people's arguments that with teaching them how to say anything constructive about the real world.
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4 of 4 people found the following review helpful
5.0 out of 5 stars top tier introduction to probability and inductive logic, May 3, 2011
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
I love this book. It is easy to read and provides excellent examples. Not only does it introduce the reader to Bayes' Theorem, but it also covers various gambler's fallacies. A nice addition is the lucid philosophical commentary that keeps the reader informed about the various debates about inductive logic that have taken place over the ages. With this book, a beginner can get up-to-date with the theorem (Bayes') that has recently taken both the philosophy of science and probability worlds by storm.

It is great to see a solid logic book for philosophy that is not deductive. Inductive logic is important too!
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4 of 5 people found the following review helpful
5.0 out of 5 stars recommended!, June 1, 2010
By 
Steve (Denver, CO) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
The author gives admirable attention to clarity for the topics discussed in this book. As an introductory text, it's not reasonable to expect completeness for the more complex topics addressed. I highly recommend this book to anyone looking for an introduction to probability and inductive logic.
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3 of 4 people found the following review helpful
5.0 out of 5 stars Brick by brick: the most plain-English logic and probability book I have seen, July 21, 2013
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PHIL (San Diego, CA, United States) - See all my reviews
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
This closely reflects my own (college law) teaching style: use the smallest words and simplest examples possible, to start with, and then add on the technical terminology. Starting from a very ad hoc knowledge of logic and probability, and wishing to become formally proficient, I have been digging through various books on these topics to find one remedial enough to suit me (and the more advanced books in my library are thus waiting for later perusal). Bingo! Some highbrows may feel this style is "spoon-fed" or "dumbed down." However, a good teacher, to my mind, is one who builds a good steady bridge from where the student actually is, to more advanced concepts, and this serves admirably.
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16 of 24 people found the following review helpful
5.0 out of 5 stars Hacking gets everything right except for Keynes, June 29, 2004
By 
Michael Emmett Brady "mandmbrady" (Bellflower, California ,United States) - See all my reviews
This review is from: An Introduction to Probability and Inductive Logic (Paperback)
Hacking's book is a job well done.He blends history,philosophy,logic,mathematics,statistics and science with wit and judicious scrutiny in general.Unfortunately,the book is slightly marred by inaccurate and/or incorrect statements about J. M. Keynes and/or his logical theory of probability.Describing Keynes as a"belief dogmatist"is way off the mark given Keynes's penchant for changing his mind as new and/or relevant information and analysis became available over his lifetime.Secondly,it is bizarre for Hacking to claim that Keynes had no use for frequency-type probability theories and jeered at the idea of relative frequency holding in the long run because in the long run we are all dead.(Hacking,pp.146-151).The only frequency theory Keynes ever rejected was that of John Venn.Keynes always considered frequency theories to be accurate and correct for some cases.However,they were not general in scope but limited in their applicability.The interested reader should consult chapter 8 of Keynes's A Treatise on Probability(1921).Finally, Keynes rejected the fallacy of long runism or conditional apriorism because of its unsound argument.The fact that in the long run some process may converge to a particular outcome in the limit offers no support to a do-nothing policy in the present.If the only available relevant evidence bearing on the probability of a proposition is frequency data then the logical probability is the same as the relative frequency estimate.The only caveat Keynes would add would be that the frequency data should have passed the Lexis Q Test for stability.
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2 of 3 people found the following review helpful
4.0 out of 5 stars It's a gem, February 10, 2013
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This review is from: An Introduction to Probability and Inductive Logic (Paperback)
I am half way through the book and found it a pleasure to read due to the insights by the author's clear and concise writing style. I disagree with some other negative reviews. I do a lot of quantitative analysis, but I don't think everyone needs to see a lot of equations to gain fundamental understanding of the important principles of probability and inductive reasoning. This book has the right balance of philosophical discussions and numerical examples to illustrate what it intends to do: introducing the two subjects. The book does a agreat job explaining the independence, conditional probabilities and the Bayes rule.
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An Introduction to Probability and Inductive Logic
An Introduction to Probability and Inductive Logic by Ian Hacking (Paperback - July 2, 2001)
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