The Drunkard's Walk: How Randomness Rules Our Lives (Vintage),   ISBN:9780307275172

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In "The Drunkard's Walk," CalTech physics professor Leonard Mlodinow goes about explaining probability and statistics in very simple terms, accessible to most anyone with a yearning to know about the subject. Each topic is discussed in its historical context, so you get a good sense of not just the all-important "what" but also who, why and how. The anecdotal presentation of the otherwise dry mathematical topics makes for an interesting, easy, and pleasurable read (without the condescending tone of similar books, e.g. Innumeracy), though without any equations, your ability to use most of the material is limited. The way Mlodinow presents the topic is certainly thought-provoking and philosophical, but I would urge the reader to remain a bit skeptical. Just as I do not believe in an invisible man in the sky, I similarly refuse to believe that everything I do subject to some other unseen force that decides at a whim whether or not I am successful or not in an undertaking.

I guess I lean pretty far to the deterministic viewpoint, but in the context of Mlodinow's arguments, I think "randomness" is a nice way of saying "ignorance." Everything is causal- the outcome of rolling dice, flipping coins, or dealing cards can be predicted with the equations that describe motion- the problem lies in not knowing precisely and exactly the initial conditions and all of the forces during the event (e.g., wind), so to make up for our ignorance we have the field of probability, which tries to use the statistics of past events to predict the future. We can abstract the simple event of flipping a coin to other things, including the most irrational and unpredictable of them all- human behavior- which is where Mlodinow eventually takes his readers. Everything in life, including driving on the highways, winning and losing in the stock market, sports, decision making, perceptions of other humans, music, movies, etc., exhibits "randomness" (also chaos - the so-called butterfly effect, which is not randomness), and we are encouraged to step back and be a little more thoughtful about what is happening around us, and, as the book is ended, to be thankful for the good fortunes we have had thus far.

Anyway, I thought this was a great book. I would recommend it to just about anyone.

Customer Rating: 

People had told me that it would change the way I look at the world, and I didn't really believe them, until I read it. I could not put it down, and recommended it to all my friends. The most interesting part was the section on how actors/musicians become famous, but the entire book is really interesting.

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Math and anything beyond the simplest logic is alien to me. I tried to stick it out for more than 100 pages, but I finally realized I wasn't understanding what the writer was talking about. Unlike many reviewers here, I enjoyed the stories and the biographies of medieval thinkers but couldn't understand all the probability language. I presume that this book will be enjoyable to people who understand statistics, probability and math. I don't and didn't finish the book.

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This is a great book on randomness and on the historical development of tools to gain insight into randomness. The author's writing style is superb, and I hope that he writes more books.

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A major complaint is that this book completely ignores insights regarding the normal curve that have been achieved during the last half century. It is certainly true that historically, prominent researchers once thought normality occurs naturally, a view stemming from reading more into the central limit theorem than is warranted. About a century ago, Karl Pearson, in his first paper on statistics, coined the term normal distribution, roughly meaning that it is the curve that we expect to find. But Pearson later concluded that this view is incorrect. While the normal curve still plays an important role, it is now known that it can be highly misleading and can result in grossly inaccurate conclusions, even with large sample sizes. A nontechnical description of these insights, why practical problems were missed for so many years, and how they can be addressed, can be found in Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy