欧宝娱乐

Jump to ratings and reviews
Rate this book

韦伪 尾萎渭伪蟿伪 蟿慰蠀 渭蔚胃蠀蟽渭苇谓慰蠀: 螤蠋蟼 畏 蟿蠀蠂伪喂蠈蟿畏蟿伪 魏蠀尾蔚蟻谓维 蟿畏 味蠅萎 渭伪蟼

Rate this book
危鈥� 伪蠀蟿蠈 蟿慰 伪蟽蔚尾苇蟼 魏伪喂 未喂伪蠁蠅蟿喂蟽蟿喂魏蠈 尾喂尾位委慰, 慰 Leonard Mlodinow 渭伪蟼 未蔚委蠂谓蔚喂 蟺蠋蟼 畏 蟿蠉蠂畏 魏伪喂 慰喂 蟺喂胃伪谓蠈蟿畏蟿蔚蟼 伪蟺慰魏伪位蠉蟺蟿慰蠀谓 蟺慰位位维 纬喂伪 蟿畏谓 魏伪胃畏渭蔚蟻喂谓萎 渭伪蟼 味蠅萎 魏伪喂 纬喂伪 蟿慰 蟺蠋蟼 蟺伪蟻伪谓慰慰蠉渭蔚 蟿畏 蟽畏渭伪蟽委伪 蠈蟽蠅谓 尾喂蠋谓慰蠀渭蔚, 伪蟺蠈 渭喂伪 蠂伪位伪蟻萎 蟽蠀谓慰渭喂位委伪 渭苇蠂蟻喂 渭喂伪 蟽慰尾伪蟻萎 慰喂魏慰谓慰渭喂魏萎 伪谓伪蟺慰未喂维. 韦慰 伪蟺慰蟿苇位蔚蟽渭伪 蔚委谓伪喂 谓伪 伪蟺慰未委未慰蠀渭蔚 蟽蠀蠂谓维 蟿喂蟼 蔚蟺喂蟿蠀蠂委蔚蟼 魏伪喂 蟿喂蟼 伪蟺慰蟿蠀蠂委蔚蟼 蟿畏蟼 味蠅萎蟼 蟽蔚 蟽伪蠁蔚委蟼 伪喂蟿委蔚蟼, 蔚谓蠋 蟽蟿畏谓 蟺蟻伪纬渭伪蟿喂魏蠈蟿畏蟿伪 蔚蟺畏蟻蔚维味慰谓蟿伪喂 魏伪委蟻喂伪 伪蟺蠈 蟿畏谓 蟿蠉蠂畏.

螚 蔚蟺喂蟿蠀蠂委伪 蟿慰蠀 伪纬伪蟺畏渭苇谓慰蠀 渭伪蟼 畏胃慰蟺慰喂慰蠉 萎 蟽蠀纬纬蟻伪蠁苇伪 -蟽蟿畏谓 蟺蟻伪纬渭伪蟿喂魏蠈蟿畏蟿伪 畏 渭慰委蟻伪 蠈位蠅谓 渭伪蟼- 伪谓蟿伪谓伪魏位维, 蔚尉委蟽慰蠀 渭蔚 蟿喂蟼 蔚纬纬蔚谓蔚委蟼 伪蟻蔚蟿苇蟼 萎 蟿畏谓 喂魏伪谓蠈蟿畏蟿伪 蟽蠂蔚未喂伪蟽渭慰蠉, 魏伪喂 蟿畏谓 蔚蟺委未蟻伪蟽畏 蟿畏蟼 蟿蠉蠂畏蟼. 螒魏蠈渭畏 魏伪喂 苇谓伪蟼 蔚蟺喂蠂蔚喂蟻畏渭伪蟿委伪蟼 蠈蟺蠅蟼 慰 螠蟺喂位 螕魏苇喂蟿蟼, 蟺慰蠀 苇蠂蟿喂蟽蔚 渭喂伪 伪蠀蟿慰魏蟻伪蟿慰蟻委伪, 委蟽蠅蟼 谓伪 渭畏谓 萎蟿伪谓 蔚尉蠅蟺蟻伪纬渭伪蟿喂魏维 喂魏伪谓蠈蟼 伪位位维 伪蟺位蠋蟼 蟺喂慰 蟿蠀蠂蔚蟻蠈蟼 伪蟺蠈 维位位慰蠀蟼. 螝伪喂 蟺蟻慰魏伪位蔚委 委蟽蠅蟼 蟽慰魏 谓伪 蟽蠀谓蔚喂未畏蟿慰蟺慰喂蔚委 魏伪谓蔚委蟼 蠈蟿喂 苇蠂蔚喂 未喂蟺位维蟽喂蔚蟼 蟺喂胃伪谓蠈蟿畏蟿蔚蟼 谓伪 蟽魏慰蟿蠅胃蔚委 蟽蔚 蟿蟻慰蠂伪委慰 伪蟿蠉蠂畏渭伪 蟺畏纬伪委谓慰谓蟿伪蟼 谓伪 伪纬慰蟻维蟽蔚喂 苇谓伪 位伪蠂蔚委慰 伪蟺鈥� 蠈,蟿喂 谓伪 魏蔚蟻未委蟽蔚喂 蟿慰 位伪蠂蔚委慰.

螣 Mlodinow 未蔚委蠂谓蔚喂 纬位伪蠁蠀蟻维 纬喂伪蟿委 慰喂 未畏渭慰蟽魏慰蟺萎蟽蔚喂蟼, 慰喂 尾伪胃渭慰委 蟽蟿慰 蟽蠂慰位蔚委慰, 魏伪喂 蟺慰位位苇蟼 维位位蔚蟼 蟺慰蟽慰蟿喂魏苇蟼 伪尉喂慰位慰纬萎蟽蔚喂蟼 蟿畏蟼 魏伪胃畏渭蔚蟻喂谓蠈蟿畏蟿伪蟼 蔚委谓伪喂 位喂纬蠈蟿蔚蟻慰 伪尉喂蠈蟺喂蟽蟿蔚蟼 伪蟺鈥� 蠈蟽慰 蟺喂蟽蟿蔚蠉慰蠀渭蔚. 螒蟺慰魏伪位蠉蟺蟿慰谓蟿维蟼 渭伪蟼 蟿喂蟼 蠄蠀蠂慰位慰纬喂魏苇蟼 蠄蔚蠀未伪喂蟽胃萎蟽蔚喂蟼 蟺慰蠀 渭伪蟼 魏维谓慰蠀谓 谓伪 魏蟻委谓慰蠀渭蔚 位伪谓胃伪蟽渭苇谓伪 蟿慰谓 魏蠈蟽渭慰 纬蠉蟻蠅 渭伪蟼, 未喂伪蠁蠅蟿委味蔚喂 渭蔚 伪渭蔚蟽蠈蟿畏蟿伪 魏伪喂 蠂喂慰蠉渭慰蟻 蟿喂蟼 伪位畏胃喂谓苇蟼 伪喂蟿委蔚蟼 蟿蠅谓 蟺蟻伪纬渭维蟿蠅谓. 螤伪蟻维位位畏位伪, 伪蠁畏纬蔚委蟿伪喂 蟿慰 渭蠀胃喂蟽蟿慰蟻畏渭伪蟿喂魏蠈 蠂蟻慰谓喂魏蠈 蟿畏蟼 蟿蠀蠂伪喂蠈蟿畏蟿伪蟼, 纬蟻伪渭渭苇谓慰 伪蟺蠈 蔚蟺喂蠁伪谓蔚委蟼 蟿味慰纬伪未蠈蟻慰蠀蟼 魏伪喂 蔚蠀蠁蠀蔚委蟼 渭伪胃畏渭伪蟿喂魏慰蠉蟼.

螒蟺蠈 蟿喂蟼 未喂伪纬谓蠋蟽蔚喂蟼 蟿蠅谓 纬喂伪蟿蟻蠋谓 渭苇蠂蟻喂 蟿喂蟼 伪蟺慰蠁维蟽蔚喂蟼 蟿蠅谓 未喂魏伪蟽蟿畏蟻委蠅谓, 畏 未喂蔚蟻蔚蠉谓畏蟽畏 蟿慰蠀 Mlodinow 蟽蠀谓伪蟻蟺维味蔚喂, 蔚魏蟺位萎蟽蟽蔚喂 魏伪喂 蔚渭蟺谓苇蔚喂. 螤蟻慰蟽蠁苇蟻慰谓蟿维蟼 渭伪蟼 渭喂伪 蟺蔚蟻喂慰未蔚委伪 蟽蟿畏谓 蟿蠀蠂伪喂蠈蟿畏蟿伪, 伪位位维 魏伪喂 苇谓伪谓 魏伪喂谓慰蠉蟻纬喂慰 蟿蟻蠈蟺慰 伪谓蟿委位畏蠄畏蟼 蟿慰蠀 魏蠈蟽渭慰蠀, 伪蠀蟿蠈 蟿慰 蟺蟻蠅蟿蠈蟿蠀蟺慰 魏喂 伪谓伪蟺维谓蟿蔚蠂慰 蟿伪尉委未喂 渭维蟼 蠀蟺蔚谓胃蠀渭委味蔚喂 蠈蟿喂 蟺慰位位维 蟺蟻维纬渭伪蟿伪 蟽蟿畏 味蠅萎 蔚委谓伪喂 蟿蠈蟽慰 蟺蟻慰尾位苇蠄喂渭伪 蠈蟽慰 蟿伪 尾萎渭伪蟿伪 魏维蟺慰喂慰蠀 蟺慰蠀 纬蠀蟻谓维蔚喂 蟽蟺委蟿喂 蟿慰蠀 蟿蟻蔚魏位委味慰谓蟿伪蟼 渭蔚蟿维 伪蟺蠈 渭喂伪 谓蠉蠂蟿伪 蟽蟿慰 渭蟺伪蟻.

260 pages, Paperback

First published May 13, 2008

2137 people are currently reading
35132 people want to read

About the author

Leonard Mlodinow

26books1,170followers
Leonard Mlodinow is an American theoretical physicist and mathematician, screenwriter and author. In physics, he is known for his work on the large N expansion, a method of approximating the spectrum of atoms based on the consideration of an infinite-dimensional version of the problem, and for his work on the quantum theory of light inside dielectrics.
He has also written books for the general public, five of which have been New York Times best-sellers, including The Drunkard's Walk: How Randomness Rules Our Lives, which was chosen as a New York Times notable book, and short-listed for the Royal Society Science Book Prize; The Grand Design, co-authored with Stephen Hawking, which argues that invoking God is not necessary to explain the origins of the universe; War of the Worldviews, co-authored with Deepak Chopra; and Subliminal: How Your Unconscious Mind Rules Your Behavior, which won the 2013 PEN/E. O. Wilson Literary Science Writing Award. He also makes public lectures and media appearances on programs including Morning Joe and Through the Wormhole, and debated Deepak Chopra on ABC's Nightline.

Ratings & Reviews

What do you think?
Rate this book

Friends & Following

Create a free account to discover what your friends think of this book!

Community Reviews

5 stars
7,367 (30%)
4 stars
9,708 (40%)
3 stars
5,384 (22%)
2 stars
1,181 (4%)
1 star
299 (1%)
Displaying 1 - 30 of 1,895 reviews
Profile Image for Lena.
Author听1 book398 followers
August 3, 2008
The Drunkard鈥檚 Walk is a book about randomness, a topic that most people, unless they happen to be mathematicians or have a strange fascination with statistics, probably don鈥檛 think too much about. As a species, in fact, we generally prefer not to dwell on randomness, but rather to assume that we are in control of much more of our lives than we actually are.

In this new book, physicist Leonard Mlodinow attempts to show why underestimating randomness is really not a good idea. He lays a foundation for this discussion by outlining the development of mathematical and scientific thought on the topic. When humans assumed all outcomes were due to the whims of the gods, there was no need for a concept of randomness. But that didn鈥檛 stop gamblers from trying to improve their odds in games of chance, and it is to them we owe a debt of understanding on the topic.

Mlodinow spices up some rather technical discussions about development of the theory with interesting personal history of the major players (including a guy who figured out his baker was cheating customers by compulsively weighing his bread for a year and noting the differences from random distribution) and numerous fascinating studies on the topic. Along the way, he makes a compelling argument that the human propensity to see patterns where there are none can get us into a great deal of trouble, as anyone who has ever lost money in the stock market has probably figured out.

It鈥檚 not just gamblers and investors who would benefit from understanding these concepts, however. Mlodinow also shows how misunderstandings of randomness and statistics can affect jury trials and medical studies and makes a compelling argument that the success of an individual business is usually far more impacted by randomness than it is by the personal talents of the CEO or movie studio head.

Much of what Mlodinow discusses in this book is highly counterintuitive. That, combined with the above mentioned desire to believe we are masters of our fate, explains in part why we so often underestimate the effect of randomness on our lives. But acknowledging the power of randomness does not disempower us, Mlodinow argues. Rather, it allows us to focus on the aspects of our lives over which we really do have control, such as how persistent we are, and not take so personally the random luck--both good and bad--that touches all of us.
Profile Image for David Rubenstein.
851 reviews2,751 followers
March 29, 2012
This is a very fun, entertaining book about the myriad ways in which random phenomena affect our lives. There is nothing really new here. As a physicist, I am already well familiar will all of the concepts introduced, concerning probability and statistics. But oh--what a variety of fascinating applications!

I love the story about the "Ask Marilyn" column in Parade Magazine. Marilyn vos Savant holds the record for the world's highest IQ. She discussed the famous "Monty Hall" problem, and got aggravated letters from 10,000 readers, including 1,000 PhD's (many mathematicians!) who claimed her analysis was wrong. Nevertheless, she was absolutely correct--people just do not have a firm grasp of probability concepts.

The book explains lots of interesting puzzles and paradoxes. For me, the best part of the book is the discussion of how statistically random events conspire to make "outliers". This comes up again and again, in understanding "genius" mutual fund managers and fast-growing mega-companies.

My only disappointment, is the book's emphasis on the so-called "normal" (Gaussian) distribution, to the exclusion of other distributions. Many economic and natural environmental events are outliers that deviate from the normal distribution, as described so well in Benoit Mandelbrot's .
Profile Image for Barbara.
1,669 reviews5,224 followers
November 1, 2021


Lots of people might think they can compute the odds that something will happen. For instance, If my favorite baseball team is playing an opponent with inferior stats I might be pretty sure my guys will win....and place a small wager. But random chance - which is the rule rather than the exception - could trip me up. A so-so batter on the other team might miraculously hit a grand slam home run! 馃槻



In this book Leonard Mlodinow explains how randomness affects our lives. For example, a publisher rejected George Orwell's book 'Animal Farm' with the remark "it's impossible to publish animal books in the U.S." And before he became successful author Tony Hillerman was advised "to get rid of all that Indian stuff." John Grisham's books were repeatedly rejected at first. And J.K. Rowling's first Harry Potter book was rebuffed a number of times. These writers persisted and eventually happened on the right publisher....but other (perhaps equally talented) authors didn't. Random chance at work!



Of course if we really want to figure out how likely it is that something will (or won't) happen we have to rely on math.



In this book Mlodinow elucidates some of the math concepts behind probability theory and statistics - a lot of which is complex and requires re-reading a couple of times (for me anyway). So I'll just give a very basic illustration.

Suppose Don picks up two coins and tosses them. He wants to know how likely it is he'll get one head. Don figures the possible outcomes are: zero heads, one head, or two heads. So, he thinks there's a 1 in 3 likelihood. Nope.



Don has to consider all the possible sequences: heads-heads; heads-tails; tails-heads; and tails-tails. Two possible outcomes yield one head - so the chances are 1 in 2 (50%).

A basic principal of probability theory is that the chances of an event happening depends on the number of ways it can occur.

Here's another example: In 1996 the Atlanta Braves beat the New York Yankees in the first two games of the World Series (where the first team that wins four games is the victor). So, what was the chance the Yankees would make a comeback and win the series - assuming the teams are equally matched? After explaining all the possible ways the Yankees could win the remaining games, Mlodinow calculates that the Yankees had a 6 in 32 chance of winning the series, or about 19%. The Braves had a 26 in 32 chance of winning the series, or about 81%. Against the odds, the Yankees won!



Mlodinow goes on to explain that - if one team was better than the other - that would weigh into the calculations and the odds would be different. This same type of reasoning can be applied to competing businesses, television shows, movies, whatever. And even if the odds favor the 'better contender', sometimes - by pure chance - the 'worse contender' will win.



Of course 'experts' try to predict all kinds of things: whether stocks will go up; if a superhero movie will be No. 1 at the box office; whether Toyotas will sell better than Buicks; if a certain horse will win the Triple Crown; and so forth. And Mlodinow explains that - no matter how 'knowledgeable' the maven - the predictions might be wrong. The reason: our brains aren't wired to do probability problems very well. 馃ゴ

In the book, Mlodinow discusses Pascal's triangle, the Bell Curve, random number generators, the best strategy for picking the 'correct door' on 'Let's Make a Deal', the likelihood a woman carrying fraternal twins will have two girls, whether scolding a worker who does badly and praising a worker who does well makes a difference in their future performance, one man's strategy for winning at roulette....all kinds of interesting stuff.


Pascal's Triangle


Bell Curve


Let's Make A Deal


Twins

The book is informative and contains a lot of fascinating stories about the philosophers and mathematicians who developed probability theory, how they did it, and why (usually having something to do with gambling.... ha ha ha). I enjoyed the book and would recommend it to readers interested in the subject.

You can follow my reviews at
Profile Image for Trevor.
1,472 reviews24.1k followers
September 7, 2009
I hadn鈥檛 realised I had read this guy before, and remarkably recently. was a fascinating read and oddly enough, I was even reminded of it as I was reading this one and I still didn鈥檛 put two and two together (an appropriate enough metaphor for books on mathematics) until I was well over half way through. They are very similar books 鈥� presenting an entire field of mathematics to a non-mathematical audience from an historical perspective in simple and engaging prose.

The historical perspective is very important, too. Marx said somewhere that all subjects are pretty much history 鈥� even though that has rarely been my experience. This book shows that this is the case and shows (me at least) the benefits of this approach 鈥� as someone who learns best through narrative an historical approach is just the ticket. In presenting the history of probability theory and statistics in context and through the questions that haunted the various people who contributed to the advancement of the science I feel I have a much better understanding of these subjects than I gleaned at university where I struggled to remember which formula went with which particular sting of words in the question. This guy would make a fantastic teacher: actually, he makes a fantastic teacher in both of these books.

He also points out the difference between probability and statistics, a distinction I鈥檇 never really picked up on previously. Probability is the study of data when you know a fixed probability of something. So, you can look at the results of a series of coin tosses in which all of the coins show heads given you know each toss has a 50-50 probability of coming down heads. Statistics is essentially working backwards 鈥� given a series of data how do you work out the underlying probability.

The main point in his presenting all of this maths is to discuss why humans seem quite so incapable of rationally predicting outcomes based on the data presented to them and (as the maths shows) are quite predictably irrational in the mistakes they make in seeking to understand the meaning of particular strings of data. This stuff is handled better and more amusingly by , and even in (the oddest quote on the back of this book is from 's author Daniel Gilbert who says this book is 鈥榦ccasionally hysterical鈥�. If you want laughs with your science, read Gilbert or even Euclid鈥檚 Window, I can assure you that you shouldn鈥檛 buy this one for the jokes).

But, having said that what this book does do is give a wonderfully simple understanding of the maths that is taken for granted by the authors of these other books and which in itself is a powerful incentive to read this book. The first chapter and last chapter of this book in particular are essential reading 鈥� the discussion of Hollywood film studio executive Sherry Lansing is instructive in both showing how much we overstate the affect 鈥榣eaders鈥� have in the success of a company and also how we blame them and praise them for things that are probably little more than random noise. The notion that is reiterated throughout this book that exceptional performances are just that, that is 鈥榚xceptional鈥�, and that these exceptional performances will tend to be followed by a more average performance is a lesson we would all do well to learn.

And here is why, what about this question? Is it better to praise someone after they have done something well or to severely criticise them after they have done something badly? Scientific studies looking at this question show unequivocally that praise is better than criticism. But is that what we do? People actually have good reason to do the exact opposite of what is proven to be the better technique of obtaining better performance. You see, if someone does something exceptionally well and you praise them for it their next attempt (given their previous attempt was 鈥榚xceptional鈥�) is likely to tend towards the mean 鈥� that is, it is likely to be worse than their previous go. People being what they are (creatures that are determined to see causal relationships even where none exist) will therefore conclude that their praise encouraged the high performer to 鈥榮lacken off鈥� and to therefore do worse in the task the next time it was performed. But now look what happens the other way. Someone, just as randomly, does particularly badly at a task 鈥� so you scream at them and 鈥榳ear their guts for garters鈥� as the expression goes. What is likely to happen the next time they do the task? Well, they are likely to also find their performance tends back toward the mean 鈥� that is, they will apparently get better at the task. So 鈥榚xperience鈥� teaches us the exact opposite of what is the best method of achieving better performances from the people we are instructing 鈥� rather than ever praising people, 鈥榚xperience鈥� tells us to never reward good performance and only to ever punish poor performance. And this is all the case because 鈥榚xperience鈥� is wrong due to us misunderstanding the lessons of randomness.

This misunderstanding isn鈥檛 just the case in the pedagogical curiosity discussed above, but is much more general. We praise CEOs when the stock price goes up and sack them when it goes down, we delight when opinion polls have our favourite party gaining a percentage point in the popularity stakes and find ourselves in the doldrums when their fortunes fade by the same amount (even when the error in these polls can be as high as three percentage points and so these 鈥榮hifts鈥� are actually completely meaningless) and we put people in prison because there is only a one in a million chance someone else did it, when there are three million people in the city where their crime took place. There are very disturbing consequences to our not understanding statistics, to our not understanding randomness.

If you read and could not follow the odd part in that story about changing your bet if you are on Let鈥檚 Make A Deal you should get this book. (Briefly, if there are three doors, only one with a good prize behind it and after you have made your selection the host discloses that behind one of the two doors you didn鈥檛 pick there is a rubbish prize 鈥� if you get the chance to change your selection, you should. I know, it doesn鈥檛 make sense, I know it sounds like your chance is still 50-50, but that is part of the reason why you should read this book).

Gamblers generally ought to read this book. You will see (actually, you probably wont see anything of the kind, as gamblers are just as fooled by 鈥榚xperience鈥� as the bad teacher discussed above) that we are constantly fooled by what we 鈥榢now鈥� is true, even when it isn鈥檛. I remember talking to a guy who was explaining to me how he played two-up 鈥� a particularly Australian gambling game involving two coins. He told me about a time he won lots of money because heads kept coming up and so he shifted his beating because tails were 鈥榙ue鈥�. Okay, so he won money, but not for the reasons he thought and there was no way I would ever have convinced him of this. You see, while there is a law of large numbers in probability theory 鈥� that is, if you toss a coin a very large number of times then if the coin is true it will tend to land 50% of the time on heads 鈥� there is no corresponding law of small numbers. And the mere fact that the coin has landed on heads for five or even fifty flips in a row does not mean tails is 鈥榙ue鈥�. The fact we are so easily fooled by this is one of the main points behind this book.

There are lovely explanations in this of Pascal鈥檚 Triangle and how this develops into the normal distribution curve. Fascinating and frightening discussions of false positives and biases that we invariably fall for. Then there are also topics on how we are manipulated and cheated because of our limited understanding of how randomness affects our lives. I鈥檓 finding that I can鈥檛 get enough of this topic at the moment 鈥� I鈥檓 hesitating, mostly due to not having the time, to buy a good book on statistics, it is nearly 30 years since I was taught this stuff at university and it might be finally time I learnt it properly.

This is an essential companion book to so many other books on the topic of randomness and the consequences of randomness in how we understand (and misunderstand) our lives. I really enjoyed it and will now have to track down other books by this Mlodinow guy (and perhaps even try to remember his name so that I realise I am reading one of his books when I do.)
Profile Image for aPriL does feral sometimes .
2,110 reviews497 followers
February 3, 2021
There is a lot that is disturbing in 'The Drunkard's Walk: How Randomness Rules our Lives.' by Leonard Mlodinow. Are we 'Masters of the Universe'? Not so much.

The author discusses in a breezy, easy to understand conversational manner how randomness and chance are behind many human decisions. We believe we make decisions based on educated guesses or personal skills. Luck, though, functions far more than we know in how things turn out for us.

Briefly, but entertaining all the while, the author discusses famous incidents which illuminate the psychology behind mistaken beliefs of 'winning'. He discusses as an overview the math which makes obvious how rules of chance control planned success, or how choices can be better made if one understands the probability of a choice's odds of happening. Each chapter covers an aspect of randomness and the math that helps expose it or measure it. A brief biography of the people who created a part of this interesting class of math is also included.

Many of the chapters show how what appears to be the results of rationalized planning or expert decision-making which resulted in successful conclusions are not that, but instead are simply random luck, measurable by probability or statistical math.

It's eerie because in explaining why so many things actually occur vs. how your brain perceived the occurrence, the book leaves you with feelings that are similar to the feelings that happen when a promotion is given that you assume is because of your excellent record - but it turns out to be because none of your rivals showed up due to a car crash on the highway. Complicating efforts to get on top of luck by increasing it in your favor by learning probability math, it appears to be so difficult of an exercise in logic in some cases that expert mathematicians flub it. The author demonstrates all of this in a couple of chapters.

The conclusion is that people are truly mere automata with delusions of grandeur. Yet through all of the illusions we create to feel we have more control and power over human events than we actually do, somehow through math and crunching numbers in formulas these same lame brains of ours are able to 'see' reality. Which we totally ignore to live and function happily in a deluded state of controlling the events of our lives. Does that bother you as much a it bothers me?


Trailer on YouTube for the movie, "The Matrix":


Profile Image for Angie Boyter.
2,217 reviews84 followers
November 18, 2011
I have a math background and an interest in the mind and enjoyed reading books like Predictably Irrational and Thinking, Fast and Slow. Given Mlodinow's reputation as a physicist, I expected a reasonably sophisticated presentation, albeit one that did not require a heavy math background. I was prepared for the book to be basic and probably start with the rudiments of probability, but the presentation is SO basic that the title term "drunkard's walk" does not even occur in the book until page 176 (out of only 219 pages).
This seemed more like a history of probability and statistics (an interesting one, I'll admit, with lots of amusing anecdotes about celebrities past and present), with a bit of discussion of probability thrown in. I understand that many writers are reluctant to present a lot of equations in books for the general public, but the result in this case is that Mlodinow makes general statements but never carries the explanation far enough to satisfy curiosity or be useful. He says (p 108) "The key to understanding randomness and all of mathematics is not being able to intuit the answer to every problem immediately but merely having the tools to figure out the answer." Despite the claim on the back of the book that "Mlodinow gives us the tools we need to make more informaed decisions", he fails to provide the reader tools, instead being content to tell us which historical figures developed the tools that are in use today. This can make interesting reading, but it is not what was advertised.
Profile Image for Bronson.
87 reviews21 followers
October 26, 2013
Yes, I was an English major so, yes, I LOVE literature, but my statistics courses were my favorite courses ever. I can't claim to be an expert statistician since I haven't run a chi-square analysis in eons and since I can only remember the phrase "data set" but can't remember how to collect one (kidding), but COME ON! Some of Mlodinow's information is interesting, but much of his logic seems unfounded and certainly begs some sort of question (and often a rather basic one at that). I've only finished 1/3 of it, and I'm sure it has a wonderful ending for those with sadistic fortitude, but (statistically speaking) the likelihood of me completing any more of it is about eight deviations to the left on the s-curve, if ya' know what I'm sayin'. Sheesh.
Profile Image for Paul Weiss.
1,425 reviews464 followers
December 23, 2023
A unique approach to a difficult subject!

Mathematicians or, at least, those comfortable with mathematics will probably suggest that A DRUNKARD'S WALK offers little new to them in terms of concrete mathematical analysis that they weren't already familiar with. And I'm certainly inclined to agree.

On the other hand (even as a graduate of a university program in applied math and theoretical physics), I found plenty of interest and a remarkable level of insight demonstrating how non-intuitive the correct approach to the evaluation of probability, statistics and the almost all-encompassing effects of randomness in real-life actually is. Mlodinow offers plenty of meaty examples to chew on that are drawn from a myriad of real world arenas - the stock market, sports, consumer preferences and sampling surveys, the ways in which defense and prosecution attorneys can lead judges and juries down mathematically irrelevant and entirely spurious garden paths, medical testing, misplaced blame or unearned congratulations for strings of failures or successes that are nothing more than random variation and much, much more. Mlodinow also gives his readers some fascinating insights into how the basic nature of human psychology is, in many cases, the fundamental reason for our misinterpretation of probabilities and statistics ... EVEN in those cases where we are well aware of the illogical underpinnings of our analysis.

In short, as long as a reader already well-versed in the mathematics of probability and statistics knows what to expect, A DRUNKARD'S WALK is sure to please. Potential readers that are more math-phobic can be assured that there isn't an equation in sight and their enjoyment of a fine contribution to a diverse non-fiction library is a slam dunk!

Paul Weiss
Profile Image for Jimmy.
Author听6 books273 followers
February 28, 2015
Let's suppose you are on Let's Make a Deal with Monte Hall. There are three doors to choose from. Behind the doors are a goat, a can opener, and a new car. You want the new car. You pick door #3. Now Monte Hall says he will trade you door #3 for door #1. First he shows what's behind door #2: a goat. Now should you trade door #3 for door #1 in the hopes of getting a new car? Here are your three choices: (A) Trade because the odds are greater of getting a new car if you trade, (B) Don't trade because the odds are less, or (C) It doesn't matter because the odds are equal. Make your choice and explain why you did so, and I will tell you if you are right. By the way, the great mathematician Paul Erdos got this wrong.

Here's another story. A pilot trainer yells at trainees who mess up and they do better landing next time, but when he praises a pilot for landing well, the trainee does worse next time. Is it better to yell? No, but you can see why coaches think it works. Odds are that the pilot who messed up will do better no matter what. Those who did well will eventually do worse.

Story #3: the probability that two events will both occur can never be greater than the probability that each will occur individually. Yet intelligent people continually think otherwise. Unless an odd detail is added. So what I am learning from this book is really about how human ignorance can occur. And I always want to be vigilant about myself and my own ignorance. I'm a Socratic believer in the idea that ignorance is at the root of all our ills.

#4: Legend has it that Paul Erdos quit amphetamines for a month and said, "Before, when I looked at a piece of blank paper my mind was filled with ideas. Now all I see is a blank piece of paper."

#5: The chances of an event depend on the number of ways in which it can occur.

#6: Try the birthday game at a party. Chances are that two people there will share the same birthday. I have done this in a classroom, and it usually works.

#7: In 1654, Fermat, he of Fermat's last theorem fame, held a high position in the Tournelle, or criminal court, in Toulouse. Pierre de Fermat is usually considered the greatest amateur mathematician of all time. But he also condemned people to be burned at the stake.

#8: For the last 8 years of Pascal's life, he committed himself to God. He sold everything except his Bible and gave his money to the poor. He wore an iron belt with points on the inside. When he was in danger of feeling happy, he pushed the spikes into his flesh. This was Pascal's Wager: Betting on the existence of God.

#9: Grading papers. I can speak from experience on this one. We had to grade papers from around the state on a scale of 1 to 4. We had examples of each. Yet some teachers gave horrible papers a 4 because they had "sincerity" or some such nonsense and others gave great papers a 1 because they were too structured.

#10: Voting recounts. Why does every recount get a different number? Great question. It never comes out the same. Says something about the system.

#11: Best way to gain 30 points on your SATs is to take the test a few more times. Law of averages means you will eventually get a better score.

#12: Wine tasting is a bit of a sham. No need to go into the details. You knew it all along, didn't you?

#13: There were 1,000 more highway fatalities after 9/11 because people were afraid of flying.

#14: Table moving in the mid 1800s was caused by the fidgeting of the participants with their hands on the table.

#15: The psychologist Bruno Bettelheim said survival in Nazi concentration camps "depended on one's ability to preserve some areas of independent action, to keep control of some important aspects of one's life despite an environment that seemed overwhelming."

#16: Nursing home residents given control of their rooms lived longer and were happier than those who had no control.

#17: Nobel laureate Max Born: "Chance is a more fundamental concept than causality."

#18: When an event is happening it is difficult to see the outcome. Later we can't understand why we didn't respond better. President Obama's measured approach is probably the best. Things happen because of many minor factors beyond the control of most people.

#19: Observers tend to have a lesser view of victims. A high view of wealthy people.

#20: Vodka has no difference in flavor whatsoever. Yet ask anyone who drinks it and they will tell you otherwise. How stupid is that?

#21: Stephen King's Richard Bachman books did not sell until people knew it was him.

#22: A final word of advice from Thomas Watson: "If you want to succeed, double your failure rate."
304 reviews3 followers
July 23, 2012
Despite the seemingly highly rated reviews this book has received, I suspect it is more of a case of this book was hard to read which means it must be good that accounts for its ratings rather than any credit to the author's writing.

The Drunkard's walk, despite Mr. Mlodinow's attempts at following Mr. Gladwell's formula, does not succeed in copying Mr. Gladwell's easy to read voice as well. First of all, although the subtitle SAYS "how randomness rules our lives," I actually found the book to be propogating the exact opposite, our lives are actually ruled by probability and math and not random at all. Second, there was no actual connecting theme in this book. It was a collection of the most random assortment of math stories that all seem to take place sometime in the 19th centuries. They were about bizarre discoveries or how math affected people's lives, I'm not exactly sure what randomness had to do with anything other than the stories did seem to be told by a drunken man.

The writing was not easy, although if it was because it was about math and required extra concentration on my part, I apologize for that. I had to reread several chapters a few times in order to understand what Mr. Mlodinow was saying. I'm not exactly sure why his book was ordered in the way it was, nor do I understand how this became a book to begin with.

The subtitle would be better renamed: 10 odd stories about math in people's lives and how none of this will affect you.

Well. I'm glad I'm done with that book.
Profile Image for Steve Bennett.
71 reviews10 followers
May 16, 2014
My mom carried a holy card of St. Jude with her at all times. St Jude is the patron saint of lost causes. This book suggests that lost causes and what the public commonly refers to failures may just have had bad luck. Mlodinow demonstrates a lot of what the world chalks up to superior skill or thorough preparation is actually due to randomness. Or as Ecclesiastics states, in perhaps less scientific but more concise terms: "I have seen something else under the sun: The race is not to the swift or the battle to the strong, nor does food come to the wise or wealth to the brilliant or favor to the learned; but time and chance happen to them all." The Western world loves to hail victors and humiliate the losers. Yet, the difference between winning and losing is often mere chance. Mike Shanahan when he was wining Super Bowls in Denver was considered one of the best NFL coaches. This year, when he was going 3-13 with Washington, was considered one of the worst coaches ever. Did his coaching skill truly change that remarkably?

Many times while reading this book, I thought it might be sending the message, "Don't try, because randomness is a bigger factor of success than skill." As in Ecclesiastics: "All is vanity. What does it profit a man all his toil under the sun?" However, the message is actually the opposite. The message is not to feel forsaken during apparent lost causes. The wheel is still in spin. Or as Tom Petty would say, "Even the losers, get lucky some time."
Profile Image for Taka.
705 reviews603 followers
June 8, 2015
Even better the second time--

This little book is just so good鈥攏ot only does it give you just enough math to make you feel curious and satisfied, it tells a ripping good story about probability theory and statistics, providing along the way compelling portraits of the eccentric scientists and mathematicians who contributed to the fields. This time, I wanted to refresh my memory of all the thorny problems probability and statistics give us (we are really, really bad at intuiting probability, as psychologists have again and again shown us).

One good refresher among many was the fallacy we make in dealing with conditional probability, mostly prominently manifested in conspiracy theories and paranoid thoughts: these events happened, therefore there is a huge conspiracy. Or close to home (for me at least): an agent hasn't gotten back to me yet, therefore she must not like my work. Probability-wise these are based on the wrong probabilities, and logically, these are equivalent to the fallacy of affirming the consequent (if P then Q, Q, therefore P). So from the valid, highly probable inference, "If there is a huge conspiracy, these events happen" or "If an agent doesn't like my work, she will not respond for a long time," we see the consequent鈥攖hese events happened, or the agent hasn't responded in a long time鈥攁nd draw the mistaken conclusion that there is a huge conspiracy. Or the agent doesn't like my work. What's wrong with this is that there are so many possible reasons why a series of events occurred other than due to a huge conspiracy, or why the agent hasn't gotten back to me in a long time (she's just busy!). In probability terms:

the probability that she he doesn't respond to me in a long time GIVEN she doesn't like my work

is high and valid, whereas:

the probability that an agent doesn't like my work given she has not responded to me in a long time

is low (because there could be all sorts of reasons why she hasn't responded to me).

Just to hammer it home, this can be illustrated with a simple example:

If you are human, you eventually die.

is a perfectly valid conditional, but

You (pointing at a squirrel) eventually die, so you (the squirrel) must be human.

is definitely not.

More importantly, what I for some reason failed to write about in my 2012 review and totally forgot about until I reread the book is Yale sociologist Charles Perrow's normal accident theory Mlodinow mentions in the last chapter, how disasters in complex systems occur when many little human mistakes just happen to coincide at just the wrong (or right鈥攄epending on your perspective) time. I was so interested in this theory that I actually bought the seminal book by Perrow himself (and duly put on the shelf for "read immediately").

Excellent, excellent book.


[Read 1/5/2012] Awesome--

This book made me admire what modern statistics鈥攁 topic I couldn't care less鈥攊s capable of doing and convinced me, like Taleb's The Black Swan and Burton Malkiel's Random Walk Down Wall Street how randomness really rules our lives and it's important to recognize chance events and not mistakenly assign them some causality that's not there. The history of probability theory and statistics Mlodinow tells in this book is nothing short of fascinating, and I was floored by the answers to some of the problems he so deftly presents.

For example:

1) there are three doors. Behind one of them is a treasure, and behind two are geese. You pick a door. The host of the show opens one of the doors you've picked and show geese behind it. Is it better to switch your choice?

The answer: yes. You will increase your probability of winning from 1/3 to 2/3. Why? Read the book to find out why.

2) The Attorney's Fallacy. Take the O.J. Simpson trial. The prosecutor argued O.J. Simpson was an abusive husband. The defense attorney Alan Dershowitz then argued that the probability of an abusive husband killing his wife is so low, the prosecutor's argument for O.J.'s propensity for violence is misguided. In more detail:

4 million women are battered annually by their husbands and boyfriends in the U.S.
Yet in 1992, a total of 1,432 women (or 1 in 2,500) were killed by their husbands or boyfriends.
Therefore, few men who beat their wives or girlfriends go on to murder them.

Convincing, but that's not the relevant probability. The relevant probability is rather: the probability that a battered wife who was murdered is murdered by her abuser. And of all the battered women murdered in 1993 in the U.S.some 90% were killed by their abuser.

Then there's the reassuring implication that success comes to you largely by random鈥攑ublication, prizes, business success, fame, etc.鈥攁nd that means the longer we persevere, the better our odds are of succeeding. As an aspiring writer, this non-deterministic paradigm of looking at the world has helped me boost my confidence and determination.

A must-read.

Profile Image for Steve.
472 reviews1 follower
August 23, 2019
I liked Leonard Mlodinow鈥檚 The Drunkard鈥檚 Walk. It鈥檚 an important reminder of those principles, studied long ago, now only distantly familiar, regarding randomness. Because our brains do such a poor job filtering data, owing to a wide assortment of cognitive biases, it鈥檚 important, it seems, to revisit the science of probability and statistics; this work achieves that end. I think it鈥檚 a better written volume than the four others I recently read on this topic.

I enjoyed recounting the Monty Hall problem to friends. There鈥檚 got to be a way to make a quick buck off that trick? Anyone have any idea how?

When I went to the library to pick up this book, I noticed a copy of A Confederacy of Dunces, by John Kennedy Toole, which I flipped through with a vigorous, yet brief, interest. When I got home, I started reading The Drunkard鈥檚 Walk. There, on p. 10, Mlodinow discusses what book? Why, A Confederacy of Dunces. The very next day, a social gathering I regularly attend announced their book club鈥檚 reading for next month: A Confederacy of Dunces. Now what are the odds of that? Anyone? Anyone? Bueller? Bueller?
Profile Image for Jamie Smith.
518 reviews102 followers
May 31, 2021
Most people are terrible at understanding the odds. Casinos are full of people who don鈥檛 realize that, in the long run, the house always wins. People who play the lotteries can buy lists of numbers that have recently come up regularly and so are 鈥榟ot,鈥� or they can buy lists of numbers that have not come up recently and are 鈥榙ue.鈥� And none of them are worth the paper they are printed on.

This book is about randomness, about learning how to interpret the probabilities we encounter in our daily lives. Mlodinow illustrates his points with interesting stories, some of which demonstrate how badly we can mislead ourselves when we decide to 鈥榯rust our gut.鈥� Humans have a remarkable ability to see patterns, but are often led astray by thinking there is a pattern when in fact it is just random noise. The stock market technique called Technical Analysis is a good example of this, yet many people today still swear by it.

It is surprising how many important decisions are made based on faulty statistical thinking. We call football coaches and CEOs geniuses when they show great short-term results, without pausing to wonder whether they are simply the result of random fluctuations, and fire them when the same short term variations turn downward.

If you ever have to listen to a bore at a dinner party drone on about the 鈥榥ose鈥� of the wine, about its beguiling, earthy notes of acidic red and black berries with insouciant undertones of vanilla and sandalwood鈥�..and on and on and on, just smile and think 鈥榟umbug,鈥� knowing that wine descriptions are about as accurate, and about as repeatable, as horoscopes. Just adding red food coloring to white wine is enough to flummox even supposed experts. Neither you nor anyone else can really tell the difference between a $6 bottle of wine and a $60 one, so just buy the cheap stuff and 濒鈥檆丑补颈尘.

Similarly, vodka is colorless, odorless, and tasteless. Get that: tasteless. Expensive vodka does not taste any more tasteless than the cheap stuff, and yet, in 2017 Americans spent $6.2 billion on it, much of that on the high end brands. Vodka drinkers should save their money and enroll in Statistics 101.

If you ever encounter Monty Hall and he asks if you want to change the door you have chosen 鈥� do it. Mlodinow has a whole chapter explaining this, but rather than get into the details, just accept that your odds of winning increase if you change doors.

This book is not heavy on math, and the use of examples makes it easily accessible by anyone. It is a fun read, and informative to boot. We would all be healthier and wealthier if we had a better grasp of the probabilities that affect our everyday lives.

And lastly, here is a quote from the Scottish poet Andrew Lang (it鈥檚 not in the book), 鈥淗e uses statistics as a drunken man uses lamp posts鈥攆or support rather than illumination.鈥� Keep that in mind when politicians start throwing around numbers.
Profile Image for Shelley.
139 reviews16 followers
July 6, 2010
The weirdest thing about reading this book was the following:
I watched the movie "21" in which a team of college students under the tutelage of a greedy professor make tons of money in Las Vegas by counting cards while playing Black Jack. In one scene of the movie, probabilities are discussed and the professor brings up the scenario of the 3 doors on "Let's Make a Deal" and asks the class if it's better to stick with your first choice of doors AFTER the host reveals one of the doors behind which there is no grand prize or switch to the remaining door. The correct answer would be to switch but most people don't get why. Not an hour after watching this movie, I continued reading this book, which I had started earlier and within a couple of pages, the author brought up and discussed the EXACT SAME SCENARIO and the reasons why you should switch in that situation.
Talk about randomness! What are the odds on that?
I found this book very interesting but being very dense when it comes to mathematics, I got lost in several places where the author went into great mathematical detail. I liked the historical aspects of the book, his descriptions of great mathematicians (Fermat, Pascal, Newton, etc.) and how thet built on each other's work over time.
Profile Image for Justin Pickett.
503 reviews50 followers
January 13, 2024
Because of the pervasive effects of randomness in life: 1) using observed outcomes to judge people and/or their decisions is a perilous affair, and 2) success in the world depends largely on not giving up in the face of rejection鈥攐n the number of at-bats you take.

鈥淭he cord that tethers ability to success is both loose and elastic.鈥�

In the book, we learn that firing coaches after their teams suffer losses has little effect on subsequent performance, that superstar authors (e.g., Dr. Seuss, John Grisham, and J.K. Rowling) commonly started with numerous rejections (sometimes tragically, as in the case of John Kennedy Toole), that the richest people in the world (e.g., Bill Gates) can often trace their ungodly wealth to a very lucky break (sometimes one they almost squandered), that people paid to predict the stock market are modern day snake-oil salesmen, that box office success is nearly unpredictable (e.g., Star Wars was rejected repeatedly, before finally being made), and that movie stars, like Bruce Willis, frequently owe their careers to an arbitrary decision (e.g., to a move, or to go to some audition at someone鈥檚 recommendation). We also learn how little of a connection there is between brand prestige or product awards and objective quality (e.g., blind taste tests of wine or vodka often show cheaper brands tasting better). In one notable instance, some chapters from award-winning books were sent out to publishers under new author names and were promptly rejected.

What is the book like? In some parts, reviews a little of the work of Kahneman and Tversky, using everyday examples to make key points (e.g., using check-out lines in stores to discuss the availability heuristic). In other parts, he delves deep into the history of statistics and probability, covering seminal thinkers (e.g., Pascal, Bernoulli, Bayes) and their ideas (e.g., the principal of mathematical expectation, Bayesian updating and conditional probability). However, all of this material is covered in more depth and in more accessible ways elsewhere, in other books (e.g., , ).

That said, there are some super interesting parts of this book, such as the author鈥檚 discussion of the 鈥減robability guessing鈥� game, wherein you must guess what is coming next in some sequence (e.g., a sequence of alternating colors) and there are two strategies: guess the mode or try to figure out the pattern. Animals go with the former, guessing the most common color, but people tend to go with the pattern, which only works when the sequence is not random. In other words, human judgement breaks down under randomness. And, of course, randomness is everywhere and in almost everything.
Profile Image for Ints.
822 reviews82 followers
January 25, 2015
艩墨s gr膩matas liktenis man膩 gr膩matu plaukta nav apskau啪ams. Vi艈ai n膩c膩s noskat墨ties, ka viena p膿c otras tiek pa艈emtas citas gr膩matas par matem膩tiku, izlas墨tas un atliktas atpaka募. Ta膷u vi艈ai n膩c膩s gaid墨t savu k膩rtu veselus se拧us garus gadus.

M奴su dz墨ve ir pilna ar nejau拧iem gad墨jumiem, varb奴t墨b膩m un mazvarb奴t墨g膩m notikumu s膿rij膩m. Tai pat laik膩 cilv膿ka pr膩ts absol奴ti nav piem膿rots tam, lai galv膩 analiz膿tu varb奴t墨bas teorijas da啪膩dus aspektus. T膩 nav nek膩da saskait墨拧ana, kas mums padodas intuit墨vi. Cilv膿ka pr膩ts m墨l veidot sakar墨gu st膩st墨jumu par pasauli, un t膩d膿募 lielam bl膩姆im ar savstarp膿ji nesaist墨tu inform膩ciju tiks m膿模in膩ts rast skaidrojumu smuka st膩sta vied膩. Ja k膩ds cilv膿ks peln墨s daudz naudas, m膿s vi艈am pied膿v膿sim izcilas sp膿jas, ieklaus墨simies vi艈a idej膩s, tas nekas, ka algas apjoms ir gad墨juma lielums. Ta膷u m膿s neiedom膩simies, kas braucot pirkt loterijas bi募eti m奴su izredzes iet boj膩 autoav膩rij膩 ir aptuveni divas reizes liel膩kas nek膩 uzvar膿t loterij膩. 艩墨 gr膩mata ir par to, k膩 cilv膿ki gadsimtu gait膩 l膿n膩m atkl膩ja lietu patieso dabu, noskaidroja, kas ir varb奴t墨ba, un k膩p膿c m膿s psiholo模iski to nesp膿jam pareizi interpret膿t ikdienas dz墨v膿.

莫sum膩 par gr膩matu var膿tu izteikties sekojo拧i: var matem膩tiski pier膩d墨t, ka visu m奴su dz墨v膿 nosaka gad墨jums. Vari censties cik lien, bet, ja neb奴si pareizaj膩 viet膩 pareizaj膩 laik膩, nekas nemain墨sies. M膩c墨ba: nekad nepadodies, jo vair膩k m膿模in膩si, jo liel膩ka iesp膿ja b奴s atrasties pareizaj膩 viet膩 un laik膩. Tas t膩pat k膩 skol膩, ja tu esi izsities tik t膩lu, ka tevi skolot膩ji uzskata par teicamnieku, tad vari neuztraukties, t膩ds tu paliksi l墨dz skolas beig膩m. Bet visp膩r jau 拧墨 gr膩mata tom膿r ir par matem膩tiku un par to, cik 募oti cilv膿ka ikdienas pieredze ir neder墨ga, ja s膩kam run膩t par varb奴t墨b膩m.

L膿n膩m esmu non膩cis pie secin膩juma, ja autors neraksta gr膩matu kop膩 ar k膩du citu autoru, tad vi艈a darbi ir pat 募oti las膩mi. Ar墨 拧aj膩 gr膩mat膩 autors ir izvilcis gaism膩 liel膩ko da募u no v膿sturiski interesantajiem notikumiem, kas saist墨ti ar varb奴t墨bu teorijas v膿sturi. Ar墨 varb奴t墨bu teorijas pamatkoncepti tiek pasniegti interesant膩 izkl膩st膩, t膩 negarlaiko un nav p膩rv膿rsta par nebeidzamu formulu virkn膿jumu. T膩 k膩 savulaik esmu diezgan nopietni iedzi募in膩jies statistik膩, ekonometrij膩 un varb奴t墨bu teorij膩, n膩c膩s ar no啪膿lu konstat膿t, ka 募oti lielu da募u no reiz zin膩m膩 esmu pamat墨gi aizmirsis. Reiz es visas t膩s lietas, kuras autors piemin gr膩mat膩, var膿ju mier墨gi uz t墨ras pap墨ra lapas izvest pats un izv膿rsti pier膩d墨t. Tagad l墨dz t膩dam l墨menim man b奴tu nepiecie拧amas p膩ris ned膿募u laika invest墨cijas, lai visu atk膩rtotu.

Daudzlas墨t膩jiem b奴s risks saskarties ar nek膩 jauna neuzzin膩拧anu. Ar墨 es liel膩ko da募u no autora st膩st墨t膩 jau zin膩ju no citiem avotiem, un man pat rad膩s priek拧stats, ka es 拧o gr膩matu dro拧i vien jau noteikti esmu reiz las墨jis. Tom膿r ja statistika un varb奴t墨bu teorija nav tavs ikdienas intere拧u objekts, tad gr膩mata noteikti kalpos k膩 募oti labs ievads problem膩tik膩.

Gr膩matai lieku 8 no 10 ball膿m. V膿rts las墨t, ja l墨dz 拧im par varb奴t墨bu teoriju un matem膩tikas v膿sturi kopum膩 esi interes膿jies 募oti maz.
100 reviews27 followers
June 25, 2016
唳椸Γ唳苦Δ 唳膏Μ唳膏Ξ唳 唳嗋Ξ唳距Π 唳曕唳涏 唳忇唳熰 唳班Ω唳曕Ψ唳灌唳� 唳呧唳傕唳距Π唰€ 唳忇唳熰 唳Θ唰嵿Δ唰嵿Π唰囙Π 唳Δ 唳Θ唰� 唳灌Ο唳�, 唳 唳唳班Χ唰嵿Θ 唳曕Π唳� 唳曕唳� 唳Γ唳苦Δ唳� 唳ㄠ 唳曕Π唰� 唳膏 唳犩唳� 唳む唳� 唳夃Δ唰嵿Δ唳� 唳︵唳啷� 唳︵唳� 唳嗋Π 唳︵唳囙Ο唳监 唳氞唳�, 唳む唳� 唳唳唳曕唳熰唳班唳唳距Σ 唳涏Ο唳� - 唳唳唳� 唳忇Π 唳呧Θ唰嵿Ο唳ム 唳灌Μ唳距Π 唳曕唳� 唳夃Κ唳距Ο唳� 唳ㄠ唳囙イ 唳呧Η唳班 唳唳班唳唳� 唳多唳� 唳夃Κ唳唳︵唳� 唳Π唰嵿Ο唳ㄠ唳� 唳む唳� 唳灌唳む 唳灌唳膏唳むΘ唰囙Ω唰嵿Δ 唳灌Ο唳监 唳оΠ唳� 唳︵唳唰囙唰囙イ 唳椸Γ唳苦Δ 唳膏Ξ唰€唳曕Π唳�, 唳氞Σ唳�, 唳樴唳�, 唳膏唳栢唳唳� 唳栢唳侧啷� 唳膏Ξ唰€唳曕Π唳` 唳膏Μ 唳Ω唳苦Ο唳监 唳︵唳�, 唳嗋Κ唳ㄠ唳� 唳夃Δ唰嵿Δ唳� 唳嗋Κ唳ㄠ 唳唳唰� 唳唳唳ㄠイ
唳曕唳ㄠ唳む 唳 唳唳唳唳班唳� 唳膏Ξ唰嵿Κ唰傕Π唰嵿Γ唳班唳 唳︵唳�, 唳 唳樴唳ㄠ唳� 唳Σ唳距Λ唳� 唳膏Ξ唰嵿Κ唳班唳曕 唳ㄠ唳多唳氞唳� 唳灌Ο唳监 唳曕唳涏 唳Σ唳� 唳唳 唳ㄠ 唳膏唳栢唳ㄠ 唳嗋Μ唳距Π 唳曕唳膏唳� 唳椸Γ唳苦Δ?
唳唳佮唳� 唳唳� 唳涏唰嵿唳� 唳ㄠ唳曕唳粪唳� 唳曕Π唳侧 唳曕Δ 唳唳� 唳涏Ο唳� 唳夃唳, 唳唳班Ε唳� 唳Π唰€唳曕唳粪唳 唳唳� 唳唳班Σ唰� 唳Π唰囙Π 唳Π唰€唳曕唳粪唳 唳唳� 唳唳班唳� 唳膏Ξ唰嵿Ν唳距Μ唳ㄠ 唳嗋唰� 唳曕 唳ㄠ唳�, 唳忇唳熰 唳Π唳苦Μ唳距Π唰囙Π 唳唳班Ε唳� 唳曕Θ唰嵿Ο唳� 唳膏Θ唰嵿Δ唳距Θ唰囙Π 唳ㄠ唳� 唳唳侧唳班唳∴ 唳灌Σ唰� 唳む唳� 唳︵唳唳む唳 唳膏Θ唰嵿Δ唳距Θ唳熰 唳唳唰� 唳灌Μ唳距Π 唳膏Ξ唰嵿Ν唳距Μ唳ㄠ 唳曕Δ - 唳忇 唳оΠ唳`唳� 唳嗋Κ唳距Δ 唳嗋唳椸唳 唳� 唳呧Θ唳苦Χ唰嵿唳苦Δ 唳唳唳唳班唳� 唳 唳椸Γ唳苦Δ唰囙Π 唳灌Ω唰嵿Δ唳曕唳粪唳� 唳嗋唰� 唳む 唳嗋Ξ唳距Π 唳唳多唳唳� 唳灌Δ唰� 唳氞唳 唳ㄠ啷� 唳む唳� 唳膏Ξ唰嵿Ν唳距Μ唰嵿Ο唳む 唳 唳唳班唳唳唳侧唳熰 唳忇 唳溹唳ㄠ唳膏唳苦Π 唳夃Κ唳� 唳嗋Ξ唳距Π 唳曕唳Θ 唳忇唳熰 唳曕唳む唳灌Σ 唳嗋唰囙イ
唳嗋Θ唰嵿Α唳距Π 唳椸唳班唳溹唳唰囙唰� random signal processing 唳Α唳监 唳膏 唳曕唳む唳灌Σ 唳忇唳︵Ξ 唳唳犩 唳唳班 唳椸唳唰囙唳苦Σ啷� 唳む唳� 唳忇Ξ唳� 唳 唳栢唳佮唳涏唳侧唳� 唳唳栢唳ㄠ 唳呧Κ唰嵿Π唳唳多唳� 唳椸Γ唳苦Δ唰囙Π 唳膏唳班Ξ唰嵿Ο 唳呧唰嵿唳距Σ唳苦唳� 唳灌Δ唰� 唳膏唳班唳傕Χ 唳嗋唳班Γ 唳嗋Ξ唳溹Θ唳む唳� 唳夃Κ唳唳椸 唳曕Π唰� 唳曕唳涏 唳侧唳栢 唳灌Μ唰囙イ 唳唳唰� 唳椸唳侧唳� 唳忇 唳唳熰啷�
唳唳曕唳� 唳 唳Α唳监Μ唳距Π 唳膏Ξ唳 唳班唳唳� 唳侧唳栢Μ唳距Π 唳夃Κ唳曕Π唳� 唳唳唰� 唳唳� 唳忇 唳︵唳囙唳距イ 唳曕唳ㄠ唳む 唳忇 唳唳熰 唳Δ唳� 唳嗋唳距唰嵿唳苦Σ唳距Ξ 唳むΔ唳� 唳忇Ξ唳ㄠ 唳夃Κ唳曕Π唳`唳� 唳膏唳栢唳 唳唳∴唳む唳� 唳侧唳椸Σ啷� 唳多唳� 唳曕Π唳距Π 唳Π 唳呧Μ唳膏唳ム 唳忇Ξ唳� 唳灌Σ 唳班唳唳� 唳侧唳栢Δ唰� 唳椸唳侧 唳忇唳熰 唳-唳� 唳灌Ο唳监 唳唳啷� 唳忇Δ 唳忇Δ 唳囙Θ唰嵿唳距Π唰囙Ω唰嵿唳苦 唳唳唳唳� 唳嗋唰� 唳溹唳ㄠΜ唳距Π, 唳 唳膏Μ 唳侧唳栢 唳 唳Σ唳� 唳膏Ξ唰嵿Ν唳Κ唳� 唳ㄠΟ唳监イ 唳膏唳熰唳� 唳溹Θ唰嵿Ο 唳嗋唰嵿Π唳灌唳︵唳班唰� 唳唳熰 唳Α唳监Δ唰� 唳呧Θ唰佮Π唰嬥Η 唳曕Π唳イ 唳唳多唳唳� 唳曕Π唰佮Θ, 唳溹唳Θ唰囙Π 唳呧Θ唰囙 唳樴唳ㄠ 唳膏Ξ唰嵿Κ唳班唳曕 唳嗋Κ唳ㄠ唳� 唳唳� 唳о唳班Γ唳� 唳唳侧唳熰 唳唳啷�

Profile Image for Ioannis Savvas.
339 reviews48 followers
February 13, 2013
韦慰 螔维未喂蟽渭伪 蟿慰蠀 螠蔚胃蠉蟽蟿伪魏伪 蔚委谓伪喂 苇谓伪 尾喂尾位委慰 伪蟺委胃伪谓慰. 螇 渭维位位慰谓 蟺喂胃伪谓蠈. 螒位位维 蟺蠈蟽慰 蟺喂胃伪谓蠈; 螤慰位蠉 蟺喂胃伪谓蠈 萎 位委纬慰 蟺喂胃伪谓蠈; 螖畏位伪未萎 0,013 < p < 0,846. 韦蠈蟽慰 蟺喂胃伪谓蠈! 螒谓 尾位苇蟺慰谓蟿维蟼 蟿慰 蟽蟿慰 蟻维蠁喂 蟿慰蠀 尾喂尾位喂慰蟺蠅位蔚委慰蠀 慰 蟺蠅位畏蟿萎蟼 渭慰蠉 苇位蔚纬蔚 蠈蟿喂 伪蟺' 蠈位伪 蟿伪 尾喂尾位委伪 蟿慰蠀 蟻伪蠁喂慰蠉 蠈位伪 蔚委谓伪喂 芦渭维蟺伪禄 蔚魏蟿蠈蟼 伪蟺蠈 苇谓伪, 魏伪喂 伪蠀蟿蠈 蟿慰 苇谓伪 蔚委谓伪喂 蔚委蟿蔚 伪蠀蟿蠈 蟺慰蠀 未喂维位蔚尉伪 蔚委蟿蔚 苇谓伪 维位位慰, 蟿喂 胃伪 苇蟺蟻蔚蟺蔚 谓伪 魏维谓蠅; 螡伪 伪位位维尉蠅 蟿畏谓 伪蟻蠂喂魏萎 渭慰蠀 蔚蟺喂位慰纬萎 萎 谓伪 蟿畏谓 魏蟻伪蟿萎蟽蠅; 螤蠈蟿蔚 胃伪 蔚委蠂伪 渭蔚纬伪位蠉蟿蔚蟻畏 蟺喂胃伪谓蠈蟿畏蟿伪 谓伪 尾蟻蠅 蟿慰 芦魏伪位蠈禄 尾喂尾位委慰;

螝伪喂 蟽蔚 苇谓伪 final four 蟺蠈蟽慰蠀蟼 伪纬蠋谓蔚蟼 蟺蟻苇蟺蔚喂 谓伪 蟺伪委尉慰蠀谓 未蠉慰 慰渭维未蔚蟼 纬喂伪 谓伪 伪谓伪未蔚喂蠂胃蔚委 渭蔚 伪蟽蠁维位蔚喂伪 畏 魏伪位蠉蟿蔚蟻畏; 螤苇谓蟿蔚; 螖苇魏伪; 螒谓 魏维蟺慰喂慰蟼 蟽维蟼 苇位蔚纬蔚 267, 胃伪 蟿慰谓 蟺喂蟽蟿蔚蠉伪蟿蔚;

螝伪喂 伪谓 慰 渭苇蟽慰蟼 蠈蟻慰蟼 味蠅萎蟼 蔚委谓伪喂 80 蠂蟻蠈谓喂伪, 蟺慰喂伪 蔚委谓伪喂 畏 蟺喂胃伪谓蠈蟿畏蟿伪 谓伪 蠁蟿维蟽蠅 蟿伪 120, 伪谓 苇蠂蠅 萎未畏 蟺喂维蟽蔚喂 蟿慰 渭苇蟽慰 蠈蟻慰;

螣 Leonard Mlodinow 苇蠁蟿喂伪尉蔚 苇谓伪 尾喂尾位委慰 渭蔚 蟺慰位位萎 伪谓慰喂蠂蟿萎-伪谓伪蟿蟻蔚蟺蟿喂魏萎 蟽魏苇蠄畏, 魏伪胃蠈位慰蠀 渭伪胃畏渭伪蟿喂魏维, 伪蟻魏蔚蟿萎 喂蟽蟿慰蟻委伪 魏伪喂 蟺维渭蟺慰位位伪 蟺伪蟻伪未蔚委纬渭伪蟿伪 伪蟺蠈 蟿畏谓 魏伪胃畏渭蔚蟻喂谓萎 味蠅萎, 纬喂伪 谓伪 蟺蔚蟻喂纬蟻维蠄蔚喂 蟺蠋蟼 畏 蟿蠀蠂伪喂蠈蟿畏蟿伪 魏伪胃慰蟻委味蔚喂 蟿畏 味蠅萎 渭伪蟼. 螘蟺委蟽畏蟼, 伪谓 魏维蟺慰喂慰蟼 胃苇位蔚喂 谓伪 魏伪蟿伪谓慰萎蟽蔚喂 魏维蟺慰喂蔚蟼 尾伪蟽喂魏苇蟼 伪蟻蠂苇蟼 蟽蟿伪蟿喂蟽蟿喂魏萎蟼, 蠂蠅蟻委蟼 魏伪胃蠈位慰蠀 (魏蠀蟻喂慰位蔚魏蟿喂魏维) 渭伪胃畏渭伪蟿喂魏维, 胃伪 蟿慰 尾蟻蔚喂 蠂蟻畏蟽喂渭蠈蟿伪蟿慰.

螒谓 蔚委蟽蟿蔚 蟽委纬慰蠀蟻慰喂 蠈蟿喂 魏伪胃慰蟻委味蔚蟿蔚 蔚蟽蔚委蟼 蟿畏 味蠅萎 蟽伪蟼, 渭蔚蟿维 蟿畏 渭蔚位苇蟿畏 伪蠀蟿慰蠉 蟿慰蠀 尾喂尾位委慰蠀 胃伪 伪谓伪胃蔚蠅蟻萎蟽蔚蟿蔚 蟿喂蟼 伪蟺蠈蠄蔚喂蟼 蟽伪蟼 纬喂伪 蟿慰谓 魏蠈蟽渭慰. 螒位位维 渭畏谓 伪蟺慰纬慰畏蟿蔚蠀蟿蔚委蟿蔚, 纬喂伪蟿委 芦If you want to succeed, double your failure rate禄.
913 reviews478 followers
May 8, 2013
I'll admit it. I like books by and . I liked and . I know many consider these books lightweight and pseudointellectual, and that a more incisive critical reader than I am would probably make mincemeat of them. But I find them entertaining and interesting, even if they don't always hold up to critical analysis.

falls squarely into this genre, and some of the ground covered will be familiar to other readers who consume these books. is a little different, though, in that it goes beyond cognitive biases and surprising stories of successful/failed fads and geniuses to discuss statistics and probability and the fact that we tend to underestimate the influence of chance and overestimate other factors such as talent, skill, and actual appeal. This may sound depressing, but we can actually view it as encouraging. Your talent and skill may be irrelevant. But because chance is so powerful, you can increase your likelihood of success simply by refusing to give up. Odds are, if you keep trying, eventually you'll achieve the results you want through sheer luck.

resembles 's books in that the entertainment value of the examples perhaps exceeds the intellectual tautness of the connecting thesis. Still, though, this was an entertaining, readable, and interesting book which gives you a lot to think about and is fun without being a waste of time.
Profile Image for Leah.
733 reviews116 followers
October 29, 2019
Got through 80% and decided to stop lol... Couldn't take it any longer. This book is extremely dry and boring. Although there are some valuable things to learn from it.

But I thought this book was going to have more to do with psychology but it has more to do with statistics and probabilities - mathematics... And do you know what my least favorite subject was in all of my Business degree? ... Statistics... Maybe it's because I'm not interested in it, maybe because I just don't understand it, but I hated and still hate it lol I think if were to want to learn about it I'd rather it in a textbook form and not a book.
Profile Image for Maher Razouk.
753 reviews241 followers
December 18, 2020
廿賳 丕賱賰孬賷乇 賲賲丕 賷丨丿孬 賱賳丕 - 丕賱賳噩丕丨 賮賷 賵馗丕卅賮賳丕 貙 賵丕爻鬲孬賲丕乇丕鬲賳丕 貙 賵賯乇丕乇丕鬲賳丕 丕賱丨賷丕鬲賷丞 貙 丕賱乇卅賷爻賷丞 賵丕賱孬丕賳賵賷丞 - 賴賵 賳鬲賷噩丞 毓賵丕賲賱 毓卮賵丕卅賷丞 亘賯丿乇 賲丕 賴賵 賳鬲賷噩丞 賱賱賲賴丕乇丞 賵丕賱丕爻鬲毓丿丕丿 賵丕賱毓賲賱 丕賱噩丕丿. 賱匕丕 賮廿賳 丕賱丨賯賷賯丞 丕賱鬲賷 賳丿乇賰賴丕 賱賷爻鬲 丕賳毓賰丕爻賸丕 賲亘丕卮乇賸丕 賱賱兀卮禺丕氐 兀賵 丕賱馗乇賵賮 丕賱鬲賷 鬲賰賲賳 賵乇丕亍賴丕 貙 賵賱賰賳賴丕 亘丿賱丕賸 賲賳 匕賱賰 氐賵乇丞 賲卮賵卮丞 亘爻亘亘 丕賱鬲兀孬賷乇丕鬲 丕賱毓卮賵丕卅賷丞 賱賯賵賶 禺丕乇噩賷丞 睾賷乇 賲鬲賵賯毓丞 兀賵 賲鬲賯賱亘丞. 賴匕丕 賱丕 賷毓賳賷 兀賳 丕賱賰賮丕亍丞 賱賷爻鬲 賲賴賲丞 - 廿賳賴丕 兀丨丿 丕賱毓賵丕賲賱 丕賱鬲賷 鬲夭賷丿 賲賳 賮乇氐 丕賱賳噩丕丨 - 賵賱賰賳 丕賱毓賱丕賯丞 亘賷賳 丕賱廿噩乇丕亍丕鬲 賵丕賱賳鬲丕卅噩 賱賷爻鬲 賲亘丕卮乇丞 賰賲丕 賳賵丿 兀賳 賳氐丿賯. 賵亘丕賱鬲丕賱賷 貙 賱賷爻 賲賳 丕賱爻賴賱 賮賴賲 賲丕囟賷賳丕 貙 賵賱丕 賷爻賴賱 丕賱鬲賳亘丐 亘賲爻鬲賯亘賱賳丕 貙 賵賮賷 賰賱丕 丕賱丨丕賱鬲賷賳 賳爻鬲賮賷丿 賲賳 丕賱賳馗乇 廿賱賶 賲丕 賵乇丕亍 丕賱鬲賮爻賷乇丕鬲 丕賱爻胤丨賷丞.
.
Leonard Mlodinow
The Drunkard's Walk
Translated By #Maher_Razouk
2 reviews
August 10, 2008
Fascinating book ... It was interesting how many people I spoke to about this get very passionate about randomness. Many people think acknowledging randomness is denying God.

The book is a bit chatty, and needs to focus a bit more on errors people make with statistics in their personal lives ... but Mlodinow hit on an essential concept.

I liked this lesson: that successful people are lucky, but that lucky people are persistent, flexible, and brave.
Profile Image for GoldGato.
1,263 reviews38 followers
January 12, 2023
Modern society has promoted (advertised would be a better word) the idea that we can all control our lives, mostly for profitable results. The goal is to get into good schools, find a good job, create a good family, then go into a good retirement. That used to work, until about 2012 when the tides of rapid change started pulverizing the workplaces (eliminate the old, replace with the young), the healthcare industry (don鈥檛 get sick, it鈥檚 your problem), and the lost art of customer service (get an app). To top it all off, COVID unexpectedly came along and seared a path through what we thought was 鈥渘ormal鈥�. Except, there has never really been any kind of normal.

Our assessment of the world would be quite different if all our judgments could be insulated from expectation and based only on relevant data.

The COVID pandemic is a wonderful example to go along with this book about how chance affects our lives. In a well-ordered world, strong leaders would have already been prepared for such an event, with Plans A, B & C to help their citizenry. The majority failed. Like Pandora, the virus unleashed a box full of either overboard shutdowns or lackadaisical overseeing. We were upset because CHANCE had played a winning hand and won. Big time. Humans now believe they can control everything. Except, we can鈥檛 and never will. The mobile app revolution gave us the false impression that we could wear a watch, for example, to get healthier. Good for you, but that piano can still fall on your head.

鈥e all create our own view of the world and then employ it to filter and process our perceptions, extracting meaning from the ocean of data that washes over us in daily life.

A 鈥淒runkard鈥檚 Walk鈥� is a mathematical term used to describe the paths for molecules when they fly around and bump into other molecules. In other words, the very concept of randomness means that successes or failures have little to do with skill or incompetence. I have worked alongside brilliant employees who created streamlined systems and worked their tooshies off seven days a week, yet they were never promoted or given the accolades accorded to others. That鈥檚 because ability does not guarantee achievement, nor is achievement proportional to ability.

When I started reading this book, I was a bit slow on the uptake, as there鈥檚 an emphasis on mathematical probabilities. But then the author devoted a chapter to Gerolamo Cardano, a gifted mathematician from the sixteenth century, and suddenly everything started to make more sense. The final chapters are relevant to everyday randomness which had me completely involved. Does this mean you should never plan and just hope a passing wind picks you up and carries you to happiness? The author states that it is still important to plan, but to do so with open eyes. Chance and randomness may cause us grief and aggravation, but it should also make us appreciate the absence of bad luck.

For even a coin weighted toward failure will sometimes land on success.

Book Season = Year Round (visions of illusions)


Profile Image for Robert Delikat.
197 reviews39 followers
February 21, 2014
You鈥檙e presented with three doors. Behind one door is a car and behind the other two doors are goats. Sound familiar? It is. You pick door number one. Instead of opening your choice, Monty opens door number two and reveals a goat. He then asks you if you wish to keep what鈥檚 behind your original choice (door one) or change your mind to door number three. If you think it makes no difference whether you switch or not and that your odds are 50/50 either way, you might be surprised at the answer and enjoy reading this book. If you are surprised by the answer to this ridiculously simple challenge, you鈥檙e in for a plethora of awakenings about the assumptions we make of the numbers and statistics we hear in our daily lives.

Peppered with charm and wit; wonderfully read by Sean Pratt, I would highly recommend this title to anyone interested in a history of the development of statistics. Books about numbers are especially not easy ones to listen to but Sean Pratt reads this one at just the right pace and with just the right inflections to make listening to and learning from The Drunkard鈥檚 Walk totally accessible. I will often read two or three books at a time. This one, however, was just so captivating, it monopolized my complete attention. But then I鈥檓 a nerd and that too might be a requirement for truly enjoying this title.
Profile Image for Dan.
1,247 reviews52 followers
February 21, 2022
3.5 stars

I liked some of the anecdotes and don't disagree with any of the statistical assertions. It is even okay that there is no math presented. But the book does not measure up to the to the likes of Gladwell's Blink or Levitt's Freakonomics.

I think the main reason for the lack of entertaining insights here is that the author is a physicist and not an economist or social scientist. So instead it is a book by a physicist who is not really working in this field with a lot of collaborators in economics or social sciences. So the anecdotes are kind of simplistic in comparison and we don't see provocative chapters like those in Freakonomics including the telltale marks of a cheating schoolteacher or the secrets of the Ku Klux Klan or comparing pimps to real estate agents. The author did try a social experiment where he wrote his fifteen year old's term paper and only received a 93. So there is some effort at anecdotes here.

I did enjoy the brief history that the author presented when discussing the likes of Pascal, Bernoulli, etc. I thought these were the best parts of the book.
Profile Image for Emma Sea.
2,214 reviews1,199 followers
May 6, 2013
Not as much fun as I hoped.

I didn't expect as much on the historical development of different statistical techniques and theorems: I thought there'd be more emphasis on the randomness in our day to day lives. Where this was the focus I thought the book was great: aspects like false positive HIV tests and film studio performance, for example. For this reason I enjoyed the final two chapters vastly more than the rest of the book.

wrote an incredibly comprehensive review which sums it all up nicely.

2.5 stars, rounded down.
Profile Image for Aaron.
309 reviews47 followers
December 18, 2011
Overall I'll give it to Leonard Mlodinow for writing a math book that's surprisingly accessible to the general public. Well, maybe it's not exactly a math book, or even a statistics book. But there's a fair amount of each and he did a fine job with keeping it generally light and interesting.

Mlodinow explains that there are basically two definitions of random, and they don't always go together (pp. 84-85). The first is by Charles Sanders Peirce and basically states that a process or method is truly random if given enough tests, trials, samples, examples any outcome is equally likely as any other (the "frequency interpretation of randomness"). In other words, regardless of how things seem (especially when you're only looking at very little data), there's nothing "special" going on that prefers or encourages one result over another. Mlodinow doesn't go in this direction, but I would say most people would relate this to/understand this in terms of neutrality, equality, fairness, balance, impartiality, etc. Setting aside debates in cognitive psychology and linguistics about modules and association, let's just say that most people would say these things are important (ideally) in business, law, politics - anywhere where people and things should be treated the same. Mlodinow then offers the second common definition of randomness, the "subjective interpretation," where "a number or set of numbers is considered random if we either don't know or cannot predict how the process that produces it will turn out." Again, he doesn't take this road, but I think most reader would relate this to things like luck, whimsy, risk, guess, judgment, odds, choice, etc.

You'd think that he'd establish these weird heavy definitions and and run with them for another 200 pages. But he doesn't. He leaves these definitions orphaned on pages 84-85, which is a shame because they seem to be the most interesting and relevant part of the whole book. What was the purpose of bringing them up at all? Better question is What is the purpose of the book? Sure, to sell books, makes some cash, and better inform the public. But more than that I think this book somewhat aims at the "big dreamers," those people who seek big success, or at least dream about it, and want to know why it works. Or why it doesn't. Mlodinow uses a fair number of examples of business stories, Hollywood stories, scientist stories, and gambling stories. It's not a glorification attempt, but to illustrate that luck has a lot to with it. From Bill Gates to Bruce Willis, Stephen King to Anne Frank, Thomas Edison to George Lucas, luck plays a role as much as hard work. He offers the advice to persevere to those who aim to succeed because often not bad talent but bad luck that fails you. Okay, fair point. I think this is the kind of stuff that people want in such books so it's included for "sentimental" reasons, but it doesn't tell us anything we don't already know.

What is interesting to me is the discussion of why we believe what we do and how we act accordingly. Mlodinow discusses factors that influence our perceptions and our ideas. He references a few studies, including Daniel Kahneman intuition studies and Melvin Lerner's Just-world phenomenon, but he doesn't really go into the details. In particular he glosses over part of Kahneman's study and overlooks a point that's essential to his own book. On page 22 he reports finds of a fictional character "Linda" described with, I guess you could call it, hippie or generally leftist leanings, and participants ranked the likelihood of 8 statements:

1. Linda is active in the feminist movement.
2. Linda is a psychiatric social worker.
3. Linda works in a bookstore and takes yoga classes.
4. Linda is a bank teller and active in the feminist movement.
5. Linda is a teacher in an elementary school.
6. Linda is a member of the League of Women voters.
7. Linda is a bank teller.
8. Linda is a insurance salesperson.

The point here was that number 4 includes number 7, but was ranked as more likely. Mlodinow used this study to show that intuition is not a reliable judge and that people tend to make obvious mistakes once they get an idea in their head. (Specifically, Kahneman demonstrated that people are more likely to believe something is the case when additional, even irrelevant information is provided. But I read something else in this study - that people probably take number 7 to mean "Linda is a bank teller, but not a feminist." Maybe the original study specifically controlled for this (I doubt it), but the point is that number 7 is not "neutral" or "interchangeable" with other items. Whether she is a bank teller seems (to some degree) to be relevant to her social-political identity, as much as any of the other items suggest. For example, if they use "Linda's new shoes are blue," or "Linda was born in July," people would say they're both totally irrelevant to the description and uninformative to where they should rank. Is this really a relevant point? Maybe, maybe not. But I bring it up to show how difficult it is to really identify what people take into consideration when making decisions, which is a big part of what the book is about - given the fact that so much is outside our control, awareness, or understanding, how do we choose wisely?

A fair amount of the book is dedicated to math and statistics. I think most people will find it manageable, or can safely skip over anything technical without missing much. About half of it is really "about" the first definition above (frequency) - and that's the heavy math stuff. The other half is about how people act and think when there is not enough information to know better, and what goes into that thinking. I don't know if this would do much to really change how people think about chance, statistics or randomness, as he seemed to specifically avoid technical issues. Most people will probably just fit each case covered into their present ideas of any of those italicized words I put after each definitions. Those are the real concerns I think most people have on this topic, and he did a fair job covering them.

I wouldn't call this a social science classic, but it was entertaining and easy enough to get through.
Profile Image for Jiwesh.
30 reviews1 follower
December 6, 2021
A more concrete book on behavioural economics, statistical fallacies and randomness. Uses more math and less examples than the more-popular books on the same subject.

The book might be better suited to people who've already come across material on behavioural economics.

"We miss the effects of randomness in life because when we assess the world, we tend to see what we expect to see. We in effect define the degree of talent by degree of success and then reinforce our feeling of causality by noting the correlation."
Profile Image for 耻辞蝉莎蓯厂 .
338 reviews
May 31, 2016
A great little book about statistics (my college minor), written by a professor of physics (my major field of study).

I got my minor 11 years ago and haven't used statistics since. I've been aiming to take it back up again. maybe even do a career switch to data science (sometime down the road, at least two textbooks and a few online courses away - not to mention that I don't know of any data science openings in my city and I love my current house, and so does my husband...). I figured that plunging myself into pop books on the subject might be a good start.

From a technical point of view, there's not much to be gained from this book. I don't recall seeing even a single formula. However, it's kind of impressive that a professor of physics could write a book about statistics without using any formulas. Well, he has written for Star Trek and MacGyver afterall...

Definitely a good historical account of statistics and statisticians, which I'd had only brief exposure to before. Also, I liked how he kept pointing out that probability/statistics/randomness can really influence our experience of our own lives. For instance, Mlodinow's own father lost his first wife and children to the holocaust. But, had that not happened, his father would never have married Leonard's mother (also a holocaust survivor), and Leonard would not exist. Obviously, someone with that background must have spent considerable time thinking about such dichotomies as meaning and randomness.
Displaying 1 - 30 of 1,895 reviews

Can't find what you're looking for?

Get help and learn more about the design.