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Não estamos preparados para lidar com o aleatório – e, por isso, não percebemos o quanto o acaso interfere em nossas vidas. Citando exemplos e pesquisas presentes em todos os âmbitos da vida, do mercado financeiro aos esportes, de Hollywood à medicina, Mlodinow apresenta de forma divertida e curiosa as ferramentas necessárias para identificar os indícios do acaso. Como resultado, nos ajuda a fazer escolhas mais acertadas e a conviver melhor com fatores que não podemos controlar. Prepare-se para colocar em xeque algumas certezas sobre o funcionamento do mundo e para perceber que muitas coisas são tão previsíveis quanto o próximo passo de um bêbado depois de uma noitada...

264 pages, Paperback

First published May 13, 2008

Leonard Mlodinow is a physicist and author.

Mlodinow was born in Chicago, Illinois, in 1959, of parents who were both Holocaust survivors. His father, who spent more than a year in the Buchenwald death camp, had been a leader in the Jewish resistance under Nazi rule in his hometown of Częstochowa, Poland. As a child, Mlodinow was interested in both mathematics and chemistry, and while in high school was tutored in organic chemistry by a professor from the University of Illinois.

As recounted in his book,*Feynman's Rainbow*, his interest turned to physics during a semester he took off from college to spend on a kibbutz in Israel, during which he had little to do at night beside reading *The Feynman Lectures on Physics*, which was one of the few English books he found in the kibbutz library.

While a doctoral student at the University of California, Berkeley, and on the faculty at Caltech, he developed (with N. Papanicolaou) a new type of perturbation theory for eigenvalue problems in quantum mechanics. Later, as an Alexander von Humboldt Fellow at the Max Planck Institute for Physics and Astrophysik in Munich, Germany, he did pioneering work (with M. Hillery) on the quantum theory of dielectric media.

Apart from his research and books on popular science, he also wrote the screenplay for the film*Beyond the Horizon* (currently in production) and has been a screenwriter for television series, including *Star Trek: The Next Generation* and *MacGyver.* He co-authored (with Matt Costello) a children's chapter book series entitled *The Kids of Einstein Elementary.*

Between 2008 and 2010, Mlodinow worked on a book with Stephen Hawking, entitled*The Grand Design.* A step beyond Hawking's other titles, The Grand Design is said to explore both the question of the existence of the universe and the issue of why the laws of physics are what they are.

Mlodinow currently teaches at Caltech and is in discussions about producing a book with the controversial spiritualist Deepak Chopra.

Mlodinow was born in Chicago, Illinois, in 1959, of parents who were both Holocaust survivors. His father, who spent more than a year in the Buchenwald death camp, had been a leader in the Jewish resistance under Nazi rule in his hometown of Częstochowa, Poland. As a child, Mlodinow was interested in both mathematics and chemistry, and while in high school was tutored in organic chemistry by a professor from the University of Illinois.

As recounted in his book,

While a doctoral student at the University of California, Berkeley, and on the faculty at Caltech, he developed (with N. Papanicolaou) a new type of perturbation theory for eigenvalue problems in quantum mechanics. Later, as an Alexander von Humboldt Fellow at the Max Planck Institute for Physics and Astrophysik in Munich, Germany, he did pioneering work (with M. Hillery) on the quantum theory of dielectric media.

Apart from his research and books on popular science, he also wrote the screenplay for the film

Between 2008 and 2010, Mlodinow worked on a book with Stephen Hawking, entitled

Mlodinow currently teaches at Caltech and is in discussions about producing a book with the controversial spiritualist Deepak Chopra.

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August 3, 2008

The Drunkard’s 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’t 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’t 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’s 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.

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’t 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’s 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.

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 The (Mis)Behavior of Markets.

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 The (Mis)Behavior of Markets.

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! 😲

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. 🥴

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.

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 http://reviewsbybarbsaffer.blogspot.com/

September 7, 2009

I hadn’t realised I had read this guy before, and remarkably recently. Euclid's Window The Story of Geometry from Parallel Lines to Hyperspace was a fascinating read and oddly enough, I was even reminded of it as I was reading this one and I still didn’t 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 – 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 – 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 – 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’d 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 – 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 Fooled by Randomness The Hidden Role of Chance in Life and in the Markets, Predictably Irrational The Hidden Forces That Shape Our Decisions and even in How We Know What Isn't So The Fallibility of Human Reason in Everyday Life (the oddest quote on the back of this book is from Stumbling on Happiness's author Daniel Gilbert who says this book is ‘occasionally hysterical’. If you want laughs with your science, read Gilbert or even Euclid’s Window, I can assure you that you shouldn’t 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 – the discussion of Hollywood film studio executive Sherry Lansing is instructive in both showing how much we overstate the affect ‘leaders’ 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 ‘exceptional’, 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 ‘exceptional’) is likely to tend towards the mean – 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 ‘slacken off’ 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 – so you scream at them and ‘wear their guts for garters’ 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 – that is, they will apparently get better at the task. So ‘experience’ teaches us the exact opposite of what is the best method of achieving better performances from the people we are instructing – rather than ever praising people, ‘experience’ tells us to*never* reward good performance and only to ever punish poor performance. And this is all the case because ‘experience’ is wrong due to us misunderstanding the lessons of randomness.

This misunderstanding isn’t 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 ‘shifts’ 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 The Curious Incident of the Dog in the Night-time and could not follow the odd part in that story about changing your bet if you are on Let’s 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’t pick there is a rubbish prize – if you get the chance to change your selection, you should. I know, it doesn’t 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 ‘experience’ as the bad teacher discussed above) that we are constantly fooled by what we ‘know’ is true, even when it isn’t. I remember talking to a guy who was explaining to me how he played two-up – 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 ‘due’. 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 – 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 – 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 ‘due’. 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’s 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’m finding that I can’t get enough of this topic at the moment – I’m 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.)

The historical perspective is very important, too. Marx said somewhere that all subjects are pretty much history – 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 – 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’d 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 – 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 Fooled by Randomness The Hidden Role of Chance in Life and in the Markets, Predictably Irrational The Hidden Forces That Shape Our Decisions and even in How We Know What Isn't So The Fallibility of Human Reason in Everyday Life (the oddest quote on the back of this book is from Stumbling on Happiness's author Daniel Gilbert who says this book is ‘occasionally hysterical’. If you want laughs with your science, read Gilbert or even Euclid’s Window, I can assure you that you shouldn’t 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 – the discussion of Hollywood film studio executive Sherry Lansing is instructive in both showing how much we overstate the affect ‘leaders’ 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 ‘exceptional’, 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 ‘exceptional’) is likely to tend towards the mean – 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 ‘slacken off’ 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 – so you scream at them and ‘wear their guts for garters’ 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 – that is, they will apparently get better at the task. So ‘experience’ teaches us the exact opposite of what is the best method of achieving better performances from the people we are instructing – rather than ever praising people, ‘experience’ tells us to

This misunderstanding isn’t 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 ‘shifts’ 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 The Curious Incident of the Dog in the Night-time and could not follow the odd part in that story about changing your bet if you are on Let’s 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’t pick there is a rubbish prize – if you get the chance to change your selection, you should. I know, it doesn’t 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 ‘experience’ as the bad teacher discussed above) that we are constantly fooled by what we ‘know’ is true, even when it isn’t. I remember talking to a guy who was explaining to me how he played two-up – 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 ‘due’. 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 – 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 – 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 ‘due’. 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’s 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’m finding that I can’t get enough of this topic at the moment – I’m 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.)

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":

https://youtu.be/vKQi3bBA1y8

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":

https://youtu.be/vKQi3bBA1y8

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.

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.

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.

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."

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."

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.

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.

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."

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."

June 8, 2015

Even better the second time--

This little book is just*so* good—not 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—these events happened, or the agent hasn't responded in a long time—and 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—depending 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—a topic I couldn't care less—is 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—publication, prizes, business success, fame, etc.—and 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.

This little book is just

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—these events happened, or the agent hasn't responded in a long time—and 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—depending 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—a topic I couldn't care less—is capable of doing and convinced me, like Taleb's

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—publication, prizes, business success, fame, etc.—and 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.

August 23, 2019

I liked Leonard Mlodinow’s *The Drunkard’s Walk*. It’s 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’s important, it seems, to revisit the science of probability and statistics; this work achieves that end. I think it’s a better written volume than the four others I recently read on this topic.

I enjoyed recounting the Monty Hall problem to friends. There’s 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’s 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’s reading for next month: *A Confederacy of Dunces*. Now what are the odds of that? Anyone? Anyone? Bueller? Bueller?

I enjoyed recounting the Monty Hall problem to friends. There’s 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

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.

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.

January 25, 2015

Šīs grāmatas liktenis manā grāmatu plaukta nav apskaužams. Viņai nācās noskatīties, ka viena pēc otras tiek paņemtas citas grāmatas par matemātiku, izlasītas un atliktas atpakaļ. Taču viņai nācās gaidīt savu kārtu veselus sešus garus gadus.

Mūsu dzīve ir pilna ar nejaušiem gadījumiem, varbūtībām un mazvarbūtīgām notikumu sērijām. Tai pat laikā cilvēka prāts absolūti nav piemērots tam, lai galvā analizētu varbūtības teorijas dažādus aspektus. Tā nav nekāda saskaitīšana, kas mums padodas intuitīvi. Cilvēka prāts mīl veidot sakarīgu stāstījumu par pasauli, un tādēļ lielam blāķim ar savstarpēji nesaistītu informāciju tiks mēģināts rast skaidrojumu smuka stāsta viedā. Ja kāds cilvēks pelnīs daudz naudas, mēs viņam piedēvēsim izcilas spējas, ieklausīsimies viņa idejās, tas nekas, ka algas apjoms ir gadījuma lielums. Taču mēs neiedomāsimies, kas braucot pirkt loterijas biļeti mūsu izredzes iet bojā autoavārijā ir aptuveni divas reizes lielākas nekā uzvarēt loterijā. Šī grāmata ir par to, kā cilvēki gadsimtu gaitā lēnām atklāja lietu patieso dabu, noskaidroja, kas ir varbūtība, un kāpēc mēs psiholoģiski to nespējam pareizi interpretēt ikdienas dzīvē.

Īsumā par grāmatu varētu izteikties sekojoši: var matemātiski pierādīt, ka visu mūsu dzīvē nosaka gadījums. Vari censties cik lien, bet, ja nebūsi pareizajā vietā pareizajā laikā, nekas nemainīsies. Mācība: nekad nepadodies, jo vairāk mēģināsi, jo lielāka iespēja būs atrasties pareizajā vietā un laikā. Tas tāpat kā skolā, ja tu esi izsities tik tālu, ka tevi skolotāji uzskata par teicamnieku, tad vari neuztraukties, tāds tu paliksi līdz skolas beigām. Bet vispār jau šī grāmata tomēr ir par matemātiku un par to, cik ļoti cilvēka ikdienas pieredze ir nederīga, ja sākam runāt par varbūtībām.

Lēnām esmu nonācis pie secinājuma, ja autors neraksta grāmatu kopā ar kādu citu autoru, tad viņa darbi ir pat ļoti lasāmi. Arī šajā grāmatā autors ir izvilcis gaismā lielāko daļu no vēsturiski interesantajiem notikumiem, kas saistīti ar varbūtību teorijas vēsturi. Arī varbūtību teorijas pamatkoncepti tiek pasniegti interesantā izklāstā, tā negarlaiko un nav pārvērsta par nebeidzamu formulu virknējumu. Tā kā savulaik esmu diezgan nopietni iedziļinājies statistikā, ekonometrijā un varbūtību teorijā, nācās ar nožēlu konstatēt, ka ļoti lielu daļu no reiz zināmā esmu pamatīgi aizmirsis. Reiz es visas tās lietas, kuras autors piemin grāmatā, varēju mierīgi uz tīras papīra lapas izvest pats un izvērsti pierādīt. Tagad līdz tādam līmenim man būtu nepieciešamas pāris nedēļu laika investīcijas, lai visu atkārtotu.

Daudzlasītājiem būs risks saskarties ar nekā jauna neuzzināšanu. Arī es lielāko daļu no autora stāstītā jau zināju no citiem avotiem, un man pat radās priekšstats, ka es šo grāmatu droši vien jau noteikti esmu reiz lasījis. Tomēr ja statistika un varbūtību teorija nav tavs ikdienas interešu objekts, tad grāmata noteikti kalpos kā ļoti labs ievads problemātikā.

Grāmatai lieku 8 no 10 ballēm. Vērts lasīt, ja līdz šim par varbūtību teoriju un matemātikas vēsturi kopumā esi interesējies ļoti maz.

Mūsu dzīve ir pilna ar nejaušiem gadījumiem, varbūtībām un mazvarbūtīgām notikumu sērijām. Tai pat laikā cilvēka prāts absolūti nav piemērots tam, lai galvā analizētu varbūtības teorijas dažādus aspektus. Tā nav nekāda saskaitīšana, kas mums padodas intuitīvi. Cilvēka prāts mīl veidot sakarīgu stāstījumu par pasauli, un tādēļ lielam blāķim ar savstarpēji nesaistītu informāciju tiks mēģināts rast skaidrojumu smuka stāsta viedā. Ja kāds cilvēks pelnīs daudz naudas, mēs viņam piedēvēsim izcilas spējas, ieklausīsimies viņa idejās, tas nekas, ka algas apjoms ir gadījuma lielums. Taču mēs neiedomāsimies, kas braucot pirkt loterijas biļeti mūsu izredzes iet bojā autoavārijā ir aptuveni divas reizes lielākas nekā uzvarēt loterijā. Šī grāmata ir par to, kā cilvēki gadsimtu gaitā lēnām atklāja lietu patieso dabu, noskaidroja, kas ir varbūtība, un kāpēc mēs psiholoģiski to nespējam pareizi interpretēt ikdienas dzīvē.

Īsumā par grāmatu varētu izteikties sekojoši: var matemātiski pierādīt, ka visu mūsu dzīvē nosaka gadījums. Vari censties cik lien, bet, ja nebūsi pareizajā vietā pareizajā laikā, nekas nemainīsies. Mācība: nekad nepadodies, jo vairāk mēģināsi, jo lielāka iespēja būs atrasties pareizajā vietā un laikā. Tas tāpat kā skolā, ja tu esi izsities tik tālu, ka tevi skolotāji uzskata par teicamnieku, tad vari neuztraukties, tāds tu paliksi līdz skolas beigām. Bet vispār jau šī grāmata tomēr ir par matemātiku un par to, cik ļoti cilvēka ikdienas pieredze ir nederīga, ja sākam runāt par varbūtībām.

Lēnām esmu nonācis pie secinājuma, ja autors neraksta grāmatu kopā ar kādu citu autoru, tad viņa darbi ir pat ļoti lasāmi. Arī šajā grāmatā autors ir izvilcis gaismā lielāko daļu no vēsturiski interesantajiem notikumiem, kas saistīti ar varbūtību teorijas vēsturi. Arī varbūtību teorijas pamatkoncepti tiek pasniegti interesantā izklāstā, tā negarlaiko un nav pārvērsta par nebeidzamu formulu virknējumu. Tā kā savulaik esmu diezgan nopietni iedziļinājies statistikā, ekonometrijā un varbūtību teorijā, nācās ar nožēlu konstatēt, ka ļoti lielu daļu no reiz zināmā esmu pamatīgi aizmirsis. Reiz es visas tās lietas, kuras autors piemin grāmatā, varēju mierīgi uz tīras papīra lapas izvest pats un izvērsti pierādīt. Tagad līdz tādam līmenim man būtu nepieciešamas pāris nedēļu laika investīcijas, lai visu atkārtotu.

Daudzlasītājiem būs risks saskarties ar nekā jauna neuzzināšanu. Arī es lielāko daļu no autora stāstītā jau zināju no citiem avotiem, un man pat radās priekšstats, ka es šo grāmatu droši vien jau noteikti esmu reiz lasījis. Tomēr ja statistika un varbūtību teorija nav tavs ikdienas interešu objekts, tad grāmata noteikti kalpos kā ļoti labs ievads problemātikā.

Grāmatai lieku 8 no 10 ballēm. Vērts lasīt, ja līdz šim par varbūtību teoriju un matemātikas vēsturi kopumā esi interesējies ļoti maz.

May 31, 2021

Most people are terrible at understanding the odds. Casinos are full of people who don’t 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 ‘hot,’ or they can buy lists of numbers that have not come up recently and are ‘due.’ 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 ‘trust our gut.’ 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 ‘nose’ of the wine, about its beguiling, earthy notes of acidic red and black berries with insouciant undertones of vanilla and sandalwood…..and on and on and on, just smile and think ‘humbug,’ 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*l’chaim*.

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 – 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’s not in the book), “He uses statistics as a drunken man uses lamp posts—for support rather than illumination.” Keep that in mind when politicians start throwing around numbers.

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 ‘trust our gut.’ 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 ‘nose’ of the wine, about its beguiling, earthy notes of acidic red and black berries with insouciant undertones of vanilla and sandalwood…..and on and on and on, just smile and think ‘humbug,’ 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

Similarly, vodka is colorless, odorless, and tasteless. Get that:

If you ever encounter Monty Hall and he asks if you want to change the door you have chosen – 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’s not in the book), “He uses statistics as a drunken man uses lamp posts—for support rather than illumination.” Keep that in mind when politicians start throwing around numbers.

June 25, 2016

গণিত সবসময় আমার কাছে একটা রসকষহীন অহংকারী একটি যন্ত্রের মত মনে হয়, যা প্রশ্ন করব কোন ভণিতা না করে সে ঠিক তার উত্তর দিবে। দুই আর দুইয়ে চার, তিন ফ্যাক্টোরিয়াল ছয় - ব্যাস এর অন্যথা হবার কোন উপায় নেই। অধরা ফার্মার শেষ উপপাদ্য পর্যন্ত তার হাতে হেস্তনেস্ত হয়ে ধরা দিয়েছে। গণিত সমীকরণ, চলক, ঘাত, সংখ্যার খেলা। সমীকরণে সব বসিয়ে দিন, আপনার উত্তর আপনি পেয়ে যাবেন।

কিন্তু যে ব্যাপারটি সম্পূর্ণরূপে দৈব, যে ঘটনার ফলাফল সম্পর্কে নিশ্চিত হয়ে কিছু বলা যায় না সেখানে আবার কিসের গণিত?

পাঁচশ বার ছক্কা নিক্ষেপ করলে কত বার ছয় উঠবে, প্রথম পরীক্ষায় ফেল মারলে পরের পরীক্ষায় ফেল মারার সম্ভাবনা আছে কি নেই, একটি পরিবারের প্রথম কন্যা সন্তানের নাম ফ্লোরিডা হলে তার দ্বিতীয় সন্তানটি মেয়ে হবার সম্ভাবনা কত - এই ধরণের আপাত আজগুবি ও অনিশ্চিত ব্যাপারেও যে গণিতের হস্তক্ষেপ আছে তা আমার বিশ্বাস হতে চায় না। তাই সম্ভাব্যতা বা প্রোবাবিলিটি এই জিনিসটির উপর আমার কেমন একটু কৌতুহল আছে।

আন্ডার গ্রাজুয়েটে random signal processing পড়ে সে কৌতুহল একদম মাঠে মারা গিয়েছিল। তাই এমন বই খুঁজছিলাম যেখানে অপ্রবেশ্য গণিতের সুরম্য অট্টালিকা হতে সারাংশ আহরণ আমজনতার উপযোগী করে কিছু লেখা হবে। পেয়ে গেলাম এই বইটি।

যেকোন বই পড়বার সময় রিভিউ লেখবার উপকরণ পেয়ে যাই এক দুইটা। কিন্তু এই বইটি যতই আগাচ্ছিলাম ততই এমনই উপকরণের সংখ্যা বাড়তেই লাগল। শেষ করার পর অবস্থা এমন হল রিভিউ লেখতে গেলে একটা বই-ই হয়ে যাবে। এত এত ইন্টারেস্টিং ব্যাপার আছে জানবার, যে সব লেখা বা বলা সম্ভবপর নয়। সেটার জন্য আগ্রহীদেরকে বইটি পড়তে অনুরোধ করব। বিশ্বাস করুন, জীবনের অনেক ঘটনা সম্পর্কে আপনার ভুল ধারণা পাল্টে যাবে।

কিন্তু যে ব্যাপারটি সম্পূর্ণরূপে দৈব, যে ঘটনার ফলাফল সম্পর্কে নিশ্চিত হয়ে কিছু বলা যায় না সেখানে আবার কিসের গণিত?

পাঁচশ বার ছক্কা নিক্ষেপ করলে কত বার ছয় উঠবে, প্রথম পরীক্ষায় ফেল মারলে পরের পরীক্ষায় ফেল মারার সম্ভাবনা আছে কি নেই, একটি পরিবারের প্রথম কন্যা সন্তানের নাম ফ্লোরিডা হলে তার দ্বিতীয় সন্তানটি মেয়ে হবার সম্ভাবনা কত - এই ধরণের আপাত আজগুবি ও অনিশ্চিত ব্যাপারেও যে গণিতের হস্তক্ষেপ আছে তা আমার বিশ্বাস হতে চায় না। তাই সম্ভাব্যতা বা প্রোবাবিলিটি এই জিনিসটির উপর আমার কেমন একটু কৌতুহল আছে।

আন্ডার গ্রাজুয়েটে random signal processing পড়ে সে কৌতুহল একদম মাঠে মারা গিয়েছিল। তাই এমন বই খুঁজছিলাম যেখানে অপ্রবেশ্য গণিতের সুরম্য অট্টালিকা হতে সারাংশ আহরণ আমজনতার উপযোগী করে কিছু লেখা হবে। পেয়ে গেলাম এই বইটি।

যেকোন বই পড়বার সময় রিভিউ লেখবার উপকরণ পেয়ে যাই এক দুইটা। কিন্তু এই বইটি যতই আগাচ্ছিলাম ততই এমনই উপকরণের সংখ্যা বাড়তেই লাগল। শেষ করার পর অবস্থা এমন হল রিভিউ লেখতে গেলে একটা বই-ই হয়ে যাবে। এত এত ইন্টারেস্টিং ব্যাপার আছে জানবার, যে সব লেখা বা বলা সম্ভবপর নয়। সেটার জন্য আগ্রহীদেরকে বইটি পড়তে অনুরোধ করব। বিশ্বাস করুন, জীবনের অনেক ঘটনা সম্পর্কে আপনার ভুল ধারণা পাল্টে যাবে।

February 13, 2013

Το Βάδισμα του Μεθύστακα είναι ένα βιβλίο απίθανο. Ή μάλλον πιθανό. Αλλά πόσο πιθανό; Πολύ πιθανό ή λίγο πιθανό; Δηλαδή 0,013 < p < 0,846. Τόσο πιθανό! Αν βλέποντάς το στο ράφι του βιβλιοπωλείου ο πωλητής μού έλεγε ότι απ' όλα τα βιβλία του ραφιού όλα είναι «μάπα» εκτός από ένα, και αυτό το ένα είναι είτε αυτό που διάλεξα είτε ένα άλλο, τι θα έπρεπε να κάνω; Να αλλάξω την αρχική μου επιλογή ή να την κρατήσω; Πότε θα είχα μεγαλύτερη πιθανότητα να βρω το «καλό» βιβλίο;

Και σε ένα final four πόσους αγώνες πρέπει να παίξουν δύο ομάδες για να αναδειχθεί με ασφάλεια η καλύτερη; Πέντε; Δέκα; Αν κάποιος σάς έλεγε 267, θα τον πιστεύατε;

Και αν ο μέσος όρος ζωής είναι 80 χρόνια, ποια είναι η πιθανότητα να φτάσω τα 120, αν έχω ήδη πιάσει το μέσο όρο;

Ο Leonard Mlodinow έφτιαξε ένα βιβλίο με πολλή ανοιχτή-ανατρεπτική σκέψη, καθόλου μαθηματικά, αρκετή ιστορία και πάμπολλα παραδείγματα από την καθημερινή ζωή, για να περιγράψει πώς η τυχαιότητα καθορίζει τη ζωή μας. Επίσης, αν κάποιος θέλει να κατανοήσει κάποιες βασικές αρχές στατιστικής, χωρίς καθόλου (κυριολεκτικά) μαθηματικά, θα το βρει χρησιμότατο.

Αν είστε σίγουροι ότι καθορίζετε εσείς τη ζωή σας, μετά τη μελέτη αυτού του βιβλίου θα αναθεωρήσετε τις απόψεις σας για τον κόσμο. Αλλά μην απογοητευτείτε, γιατί «If you want to succeed, double your failure rate».

Και σε ένα final four πόσους αγώνες πρέπει να παίξουν δύο ομάδες για να αναδειχθεί με ασφάλεια η καλύτερη; Πέντε; Δέκα; Αν κάποιος σάς έλεγε 267, θα τον πιστεύατε;

Και αν ο μέσος όρος ζωής είναι 80 χρόνια, ποια είναι η πιθανότητα να φτάσω τα 120, αν έχω ήδη πιάσει το μέσο όρο;

Ο Leonard Mlodinow έφτιαξε ένα βιβλίο με πολλή ανοιχτή-ανατρεπτική σκέψη, καθόλου μαθηματικά, αρκετή ιστορία και πάμπολλα παραδείγματα από την καθημερινή ζωή, για να περιγράψει πώς η τυχαιότητα καθορίζει τη ζωή μας. Επίσης, αν κάποιος θέλει να κατανοήσει κάποιες βασικές αρχές στατιστικής, χωρίς καθόλου (κυριολεκτικά) μαθηματικά, θα το βρει χρησιμότατο.

Αν είστε σίγουροι ότι καθορίζετε εσείς τη ζωή σας, μετά τη μελέτη αυτού του βιβλίου θα αναθεωρήσετε τις απόψεις σας για τον κόσμο. Αλλά μην απογοητευτείτε, γιατί «If you want to succeed, double your failure rate».

May 8, 2013

I'll admit it. I like books by Malcolm Gladwell and Dan Ariely. I liked Freakonomics: A Rogue Economist Explores the Hidden Side of Everything and Mistakes Were Made (But Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts. 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.

The Drunkard's Walk: How Randomness Rules Our Lives falls squarely into this genre, and some of the ground covered will be familiar to other readers who consume these books. The Drunkard's Walk: How Randomness Rules Our Lives 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.

The Drunkard's Walk: How Randomness Rules Our Lives resembles Malcolm Gladwell'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.

The Drunkard's Walk: How Randomness Rules Our Lives falls squarely into this genre, and some of the ground covered will be familiar to other readers who consume these books. The Drunkard's Walk: How Randomness Rules Our Lives 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.

The Drunkard's Walk: How Randomness Rules Our Lives resembles Malcolm Gladwell'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.

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.

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.

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.

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.

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’t get sick, it’s 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 “normal”. 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’t 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.

*…we 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 “Drunkard’s Walk” 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’s 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’s 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)

The COVID pandemic is a wonderful example to go along with this book about how

A “Drunkard’s Walk” 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

When I started reading this book, I was a bit slow on the uptake, as there’s 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.

Book Season = Year Round (visions of illusions)

February 21, 2014

You’re 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’s 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’re 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’s 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’m a nerd and that too might be a requirement for truly enjoying this title.

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’s 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’m a nerd and that too might be a requirement for truly enjoying this title.

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.

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.

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.

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

2.5 stars, rounded down.

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.

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

2.5 stars, rounded down.

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.

Mlodinow explains that there are basically two definitions of

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

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

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.

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."

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."

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.

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

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.

March 1, 2012

So this was pretty good. I had it on my to read list for awhile so I may have built it up a bit too much in my mind before getting started though because I kept waiting for the book to "pick up" in some areas. Overall though good read, really enjoyable. A lot of these anecdotes have been used before though. I think he could have come up with a few more unique scenarios. Still it was fun. I have always thought the wine ratings were a bit suss anyway.

January 14, 2014

The book is an enjoyable and accessible pop-science book about randomness. I'm not sure if the author's conclusion is that nothing ever matters but he seems to imply it.

April 20, 2021

Poucas coisas me fascinam mais do que a aleatoriedade. Desde pequenas quebras de expectativa no dia-a-dia que fazem parar e sorrir até um somatório de eventos que sobrepostos acabam por moldar nossas vidas, o acaso fornece a pitada certa de caos no nosso caminho pra deixar as coisas mais interessantes.

O autor explica de maneira bem didática assuntos de probabilidade e estatística, que podem ser totalmente contra-intuitivos. Dá uma contextualizada histórica fantástica com relação aos grandes nomes que ajudaram a humanidade a se desenvolver nessa área, mostrando de onde veio a necessidade dos conhecimentos. E são conhecimentos úteis tanto na vida cotidiana quanto na ciência, ainda mais se levarmos em conta como dados relacionados à pandemia, eleições e tantos outros assuntos são mal-interpretados atualmente.

Os últimos capítulos trazem reflexões fantásticas sobre o efeito borboleta, sobre identificação de falsos padrões na aleatoriedade e sobre vieses de confirmação que nossas cabeças às vezes geram. Valeu a pena conferir.

O autor explica de maneira bem didática assuntos de probabilidade e estatística, que podem ser totalmente contra-intuitivos. Dá uma contextualizada histórica fantástica com relação aos grandes nomes que ajudaram a humanidade a se desenvolver nessa área, mostrando de onde veio a necessidade dos conhecimentos. E são conhecimentos úteis tanto na vida cotidiana quanto na ciência, ainda mais se levarmos em conta como dados relacionados à pandemia, eleições e tantos outros assuntos são mal-interpretados atualmente.

Os últimos capítulos trazem reflexões fantásticas sobre o efeito borboleta, sobre identificação de falsos padrões na aleatoriedade e sobre vieses de confirmação que nossas cabeças às vezes geram. Valeu a pena conferir.

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