Michael BlastlandRecensioni

The book does an excellent job of explaining where published statistics come from and what meaning should be ascribed to them, with many examples. Explains how data, averages and risk factors can be deceptive or exaggerated for effect, yet shows how to interpret these numbers without throwing them out entirely.

В 1990-х годах в зоомагазинах Германии появились необычные мраморные рачки. Их главной особенностью был партеногенез (однополое размножение), в результате которого на свет появлялись идентичные клоны единственного родителя. Рачки стали подарком для биологов: те рассчитывали, что обрели много дешевых идентичных особей для экспериментов. Однако их ждал сюрприз: даже в лабораторных условиях клоны вырастали разными по размеру, окраске и повадкам. Какой-то неизвестный фактор, помимо генетики и окружающей среды, воздействовал на их развитие. У науки до сих пор нет ответа. Автор книги обнаружил, что и во многих других случаях из науки и жизни есть переменные, существенно влияющие на исход запланированного. Эта полная парадоксальных примеров книга перетрясет вашу картину мира.

How the numbers bandied about in the news can be very wrong, due as much to ignorance and carelessness as any intent to deceive.

Michael Blastland is upset that everything is not neat and tidy. That there is no guarantee of symmetry. That economies are not predictable. That genetics does not describe nearly everything about life. In his The Hidden Half, he examines a multitude of disciplines and events to show we must be missing half of what is going on, because we can’t explain them otherwise. We exist on half the knowledge we need, without knowing what we don’t know.

The book is a fast-reading and delightful collection of failures, peppered with behavioral science, which is always entertaining.

When people who have written down a position one way are interviewed as if they had chosen the opposite stance, they actively defend the position they did not take as if it were always their own. Politicians are famous for being absolutely certain of the rightness of their position one day, yet take the precise opposite position another. Every year, only one economist is correct about the performance of the economy. Every model is wrong. Nothing, it seems, is predictable.

He begins with a startling enigma, at least to scientists. The marmorkrebs is a newly discovered kind of crawfish that flourishes in the German aquarium industry. Its unique feature is that the females can lay eggs that will hatch without input from males (parthenogenesis). All you need is a female, who can lay thousands of eggs and produce thousands of offspring with DNA identical to hers. Perfect clones, in theory. And yet, the offspring come in all shapes and sizes, and variable colorings. How is this possible when their DNA is identical? Blastland says nobody knows. No answer satisfies, and it all points out that we clearly do not understand genetics after all. If more proof were needed, he points to the past decade of breakthroughs in genetic research, which have resulted in essentially nothing. Identifying genes has not changed medicine or lives anything like the predictions had it, because that is only part of the story. And we don’t know what the rest of the story is.

Man has an insatiable need to put everything in its proper place. He needs to know things are organized, measurable, consistent and predictable. And they just aren’t. But that stops no discipline working on those assumptions and making those kinds of claims. Studies in peer-reviewed journals attest to the constant flow of new, absolutely proven ideas that are just plain wrong. Some cannot be replicated. Many are just the survivors; the journals don’t publish all the contradictory failure articles. So they aren’t cited in other papers. The result is undisputed discoveries that are worthless. We see them daily, particularly in biology, genetics and medicine. As easy to disprove as they were to prove, they are soon forgotten when they prove useless.

Medicine comes in for a particular beating in The Hidden Half.

Blastland deconstructs studies to show how useless they, drugs and tests really are. He shows that 90% of drug study results are not replicable, even by the original researchers. In one specific example of pointless tests, he takes on dementia in over 65s, where a test long considered reliable can pinpoint four positive cases in 100 tests. Unfortunately, there are six cases per hundred, so it misses two of them, or one third. Far worse, it also labels 23 additional cases as positive – falsely. This means the test claims a total of 27 positives when we know there are only six. The result: nearly two dozen people suffer the stress and anxiety of becoming demented without every becoming demented. So with breast cancer and numerous other examples where failure stops no one from taking these tests. Or doctors from requiring them.

Even in detective work, we have no clue as to the right answer. It’s a lot of guesswork and assumptions that are all but completely unreliable. He gives the example motorcycle thefts in Germany, which dropped unexpectedly from 150,000 to 45,000. All kinds of theories were put forward in economics, sociology, crime rates, employment trends and so on. The truth turned out to be, of all things, helmet laws. Germany mandated helmets for motorcyclists, which kneecapped the casual theft of motorcycles. Helmets were on no one’s top ten list of causes.

There is a lot on mice. Mice used in experiments have proven to be frustrating for those keen on definitive findings. The same batch of mice, bred to have identical properties, put in identical labs, with identical conditions and food, but in geographically different facilities, have produced different results in identical tests run on them. What is it we don’t know? We don’t know. But no one can rely on test results; that much is certain.

My own favorite story of lab mice concerns the researchers. A study wanted to determine if mice could hide their pain. Researchers injected chemicals into mice legs which gave them a great deal of pain. They found that when female humans handled them, the mice grimaced freely. But when males handled them, they braced themselves and hid their suffering, putting on a brave face. They wouldn’t allow themselves to show weakness before men. This even worked when a male’s used t-shirt was left by the cage. The experiment showed two things, neither of which has to do with muse pain. The results of mice studies are colored by the sex of the researchers and are therefore unreliable. And every mouse test going back a century is invalid because it did not take into account the sex of the researchers who examined them daily if not hourly. Our unintended arrogance in announcing results of such experiments is typical of the hidden half Blastland talks about, even if he doesn’t explicitly cite this one phenomenon.

At bottom, Blastland is saying we are nowhere near as far along as we claim and like to believe. We need a little more humility and a lot less hubris. He quotes Gustave Flaubert, hundreds of years ago: “The rage for wanting to conclude is one of the most deadly and most fruitless manias to befall humanity.” We need to accept the imperfection, not of the universe, but of our knowledge of it. That would change the whole frustration index of continual failures in science.

Meanwhile, back at the marmorkrebs, the crawfish Blastland says have stymied all the experts, it instantly occurred to me while reading the prologue that there is an obvious answer. At least to me. The fact that no males participate in the reproductive cycle means the DNA of the newborns is deficient and therefore unstable. This will produce unpredictably different, if not deformed offspring, with uncertain futures. Parthenogenesis among crawfish is unnatural, and Darwin would posit that situation could not last. Defective chromosomes missing the male input will see to it the subspecies of genetically identical females does not continue. But what do I know. I’m no biochemistry researcher. I just review books.

David Wineberg

This is a book about taking risks, and why we rate some risks as much more likely than others to occur despite statistical evidence that that may not necessarily be the case (they just stick better in our minds because they are recorded in our minds in 'story form'--via first person accounts or the media--and we all know that stories stick better than plain-vanilla facts). For instance, I worried a lot when my children were small walking to school that they would be hit by a car. Statistically, that was actually less dangerous than had I driven them to school. So this is a fun book to read, and a good book to read if you've grown up parented into believing that the world is a very dangerous place.

Actually, the most dangerous time in a woman's life is childbirth (which somehow I never really considered as dangerous, but it still is, even in 2015). For men, it's those testosterone-drenched years of the 20's and early 30's. The first year of life is still dangerous. Doing drugs, driving drunk, unprotected sex within certain communities, also still is.

So this is a very interesting book to dip in and out of (if you liked Freakanomics you should like this book); I wouldn't necessarily recommend reading it cover-to-cover as I did as the statistics of each chapter do tend to glaze over after a while, but if you read a few chapters at a time in order of your own insecurities, you'll find it hard to put down. Twenty-seven chapters cover such topics as accidents, vaccinations, gambling, chance, transportation, infancy, extreme sports, crime, unemployment, money, surgery. All have their fascinating oddities. Yes, unemployment strikes more frequently than one realises because of the oddity of the way the statistics are kept--30,000 people lose their jobs; 30,000 are hired; the result is 0 change on the unemployment scale. Tell that to the 30,000 who wake up shocked to hear they are being laid off that day--obviously an underestimated risk. In the gambling chapter you learn that the least chance you have of winning is a big government lottery, a bit better is the race track, and even better is a roulette wheel (American with only one zero, as opposed to European wheels that have two zeros).

My only negative with this work was its approach using three fictional characters--Norm (described by the authors as "a fool if you like"), Kelvin ("an offensive slug") and Prudence ("a pain in the arse") used in little scenarios at the beginning of each chapter to set the stage. I could have done without them but they were inoffensive really, and the little insights I learned not only amused me but just may make me fear some possibilities a little less than I have in the past (like an asteroid hitting earth)...which would be just fine.

I find reading non fiction slow and heavy, but some of the facts in this book were amazing, and the over arching message of how we measure risk and how much it is skewed by other moral / judgemental factors was very well done. Boggle at the huge decrease in maternal mortality over the past 100 years! Wonder if it really can be true that a couple of cigerettes (which I have internalised as Evil and Dangerous) can be the same risk as a pint or two, or a burger? And cry at the story of Ignaz Semmelweis, who worked out how to save so many lives, and got mocked and committed to a mental institution.

I couldn't get through this book. I thought it would be a light-hearted, easy to read book. However, it proved to be very factual and was not at all an easy read. I suppose if you are really into comparing morbidities it would be interesting. However, if you are looking for an easy fun read, this is not the book for you.

The message of this book are that quantifying the risks we face everyday is the smart way to approach life. Looking at the data, helps us to avoid falling prey to media induced paranoias. However, while I agree with both the message and the approach, I didn't really enjoy the stories looking at the 3 'personas' that begin each chapter. While the attempt to inject some narrative into a discussion of risk and probability is definitely welcome, I didn't find these to be well particularly compelling.

Still, well worth reading as a primer on risk.½

A father's account of bringing up a son with autism.

Weakest of the books i've read recently ion this area. the pop idea of having 3 characters to represent 3 main attitudes to risk could be appealing, but just doesn't work. the anecdotes are confused and the characters, as they must be, are just stereotypes. i gave up reading those bits after a time. the rest of the book has plenty of intriguing factoids (e.g., 1 glass of wine a day will extend your life, but 2 a day will shorten it), but the discussion tends to get waffly and lacked a clear line. Tries to cover too much ground and fails, where N Silver succeeds so well.

All you need to know about numbers, counting things and how they are (mis)used by the papers and the news. Revealing, fascinating and incredibly useful read.

An episodic-reading book that can be approached in bits and pieces, but as a collection of trivial pursuits it did not enthuse me.

I'm looking forward to reading this book. The way the media, and even people who should know better, abuse numbers so as to make real risk assessment very difficult is discouraging. For example, the American Institute of Cancer Research says we should eliminate eating bacon because doing so increases our risk of colorectal cancer by 21%. That is true on the face of it and would appear startling until you ask what the baseline is. About 45 of 1000 men will get that cancer, or about 5 per 100 men. If every one of those 100 men ate bacon every day, 6 men would get the cancer, an increase of about 20%, yet actual risk -all other risk factors aside remains really quite low at 5%.(This is an example - I'm not sure of the exact numbers) The principle is the same.

I was frosted recently by the news that taking a multi-vitamin every day did nothing to prevent heart disease or increase life-span. Now my crap detector really started going into overtime. Without even reading the study I can suspect some flaws, because there is no way you can do a truly blind epidemiologic study on 160,000 women over 8 years and exclude all the other variables. Can't be done. And since there was no way to predict ahead of time which participants would be more likely to live longer than others and pair them with similar candidates, how in the world could they come to such sweeping conclusions. And this assumes their diets were absolutely equivalent in all other respects. And then to make things worse, they suggest that in order to achieve those benefits you should eat a diet rich in fiber and greens etc. etc. without a shred of evidence that it would make a whit of difference, for precisely the same reasons as the invalidity of the vitamin study.

This is a fascinating book about risk, the probability of risk in given situations, and how humans react to the idea of risk. It takes as it’s basis three characters: Norm, a man who is average in every sense of the word, and calculates risk according to the statistics; Prudence, who worries incessantly and excessively about everything – for her, the worst case scenario is also the likeliest; and Kelvin, who is arrogant and irresponsible and seems happy to take risks in all aspects of his life. These characters are placed in different settings, as the book explores the statistical chance of something bad happening, in relation to the public perception of risk. For example, scary headlines that declare things like ‘Eating such-and-such every day leads to a 20% increase in your likelihood of getting cancer.’ Scary indeed, but the book shows what that 20% risk actually works out at.

The book is written in easy to understand language, and is often amusing. It acknowledges that it’s all very well saying there’s a one in a million chance of a specific something bad happening, but that’s little comfort to the person that is that one in a million. Nonetheless, I found it oddly reassuring to be able to understand why certain situations are so scary, yet when looked at objectively, they actually pose little real danger.

It explains how probability is calculated (and discusses the reliability – or not – of the numbers), and is full of interesting anecdotes. All in all, a thoroughly enjoyable book, on a fascinating subject. Recommended.½

Nice book about risks and life expectancies, and how they are affected by different activities. See especially figures 36 and 37 at the end. Interesting that the amount of radiation received by someone 2.5km from epicentre of nuclear blast like Hiroshima is negligible!

Amusing look at the statistics of daily life -- and about the way we use statistics. This British entry chronicles the risks and probabilities of everything from birth to death. That's interesting, but what's really interesting is the degree to which our perceptions about risk vary from the reality. The book is totally non- technical, but very useful to those who are interested in thinking about the way we think. Also, in knowing how the risks of sky diving compare to, say, the risks of heroin use.

interesting essay on the abuse of statistics and numbers, written by contributors from the Economist

Lovely book about practical understanding of statistics.

An essential guide to numerate thinking and how the media allow politicians and ad-men to con us. It covers the same ground as the BBC Radio 4 programme "More or Less" that was created by the authors. Reading it all at once is a bit like listening to a whole series of podcasts one after another, so you may prefer reading a chapter a week. If you like the radio programme, you'll enjoy the book.

Preaching to the converted. Only those already interested in the manipulation of numbers especially in the media are likely to read this - and for those this is very much an entry level popular guide containing nothing new, and no detail.

However if you are vaguely curious abou thte various numbers that get bandied about in the media and haven't yet aquired the maths/logical skills to appreciate them in context then this may well be the book for you.

A few different (but all very easy not involving any formal maths) techniques are described for the process of determining if a reported number maks sense. The first technicque is simply to ask 'is that a big number' in context. 300 million sounds a lot, and for a 1 person lottery win it certainly is. For a national healthcare improvement it is not.

And this is where the book falls down. Because it assumes a level of numeracy that I think is unwarrented. How many people live in your country? Can you divide 1 number by that many? in your head whilst reading a enws story? If you can I suspect you already know to do so, and if you can't then telling you do so doesn't help. The other issue is that all of the conclusions to the examples (such as 300 million not being large for a health care budget) are unsupported. There are no references for any item, so although the authors conclude that this number which sounds large, isn't, you don't know how they reached that conclusion. Which is precisely what this book is trying to avoid. References would have helped.

Several of the techniques seem very similar and repeat information given elsewhere. Perhaps this is just the nature of such a book which grew out of a radio series, but it is annoying.

That said, it's very readable, in an easily understandable prose. the complete absense of formal sums will appeal to many lay reader (although the requirement to do basic mental arithmatic may put as many off). The chapter on Risk i particularly illuminating, as it's one that so many media outlets seem incapable of reporting or understanding properly. In place of the detailed references there is a comprehensive list of further reading material, including the seminal Huff's How to Li wih Statistics which should be require reading for everone.

]Ultimately thisbook would be of most use to journlists - forbidden from publishing anything that deviates from these simple precepts. But as that seem unlikely to happen, the best we can do is educate ourselves and read this book, or others like it.½

A lively guide, based on a BBC radio show, to how to figure out when the numbers cited in the news, etc., make sense. I knew a lot of this before, but the authors mix the information with interesting examples; this edition was revised for the US market so it uses a mixture of UK and US information. I enjoyed it, but it probably could have been a little shorter.

This book says it does not want to teach you peculiar facts that you did not know already, but make you more aware about how numbers are used. This is also its weakness: you do not get any wiser, you are just told not to be so stupid. (No, sorry, that is probably not a reasonable critique).
I will highly recommend it to journalists and politicians, who will learn a lot about how to use and present numbers, so that they inform instead of create good (but false) stories.
It is also the perfect book about numbers for someone who would never (never!) read a book about numbers. For the rest of us, it is a mildly interesting book.

Leaving aside the fact that the authors of this book sound like a location from Doctor Who ("I stared across the barren waste of the Dilnot Blastland"), reading it is a great experience. The premise is simple, but effective. All the time we are bombarded with numbers, with statistics, that we tend to take as gospel. But both the numbers themselves and the way they are used should always be subject to a little light questioning.

The authors point out how easy it is to bamboozled by very large numbers, that can be checked out with only a few moments thought. Often what is required is to put the numbers into terms we can better understand. For example, if you heard that £3.12 billion was being spent on the UK population, it sounds an immense amount. But as the authors point out, when you take around 60 million people in the UK and 52 weeks in a year, this amounts to spending £1 a week on each person - not quite as dramatic as it seems.

I've found myself being a little bit more thoughtful about the headline figures I see in the media since reading the book. The same day I saw a newspaper headline telling how some serious crime was up 50% - a huge increase. But when you looked at the actual numbers, there were only 20 more cases. Tragedies, each one, for the people involved, but still a very unlikely occurrence, blown out of proportion by the power of percentages.

Averages, too, come in for a good deal of stick. After all, the average person has less than 2 feet (think about it), so should we change the way we sell shoes in pairs? Probably not.

Very readable, always informative and often entertaining, this is a book that every politician, civil servant and ... well, everyone... should read. It is unashamedly UK-based in its examples, which I guess explains why there isn't a US edition - but that shouldn't put anyone off. The message is universal.

Not as interesting as I had hoped. There were some useful explanations of statistics, and a few interesting examples, but I didn't actually learn much. Nor were there as many examples as I had thought a book like this would include.

De meeste mensen hebben een bovengemiddeld aantal voeten. Maar geen paniek. Michael Blastland en Andrew Dilnot proberen in hun boekje ‘The tiger that isn’t’ dit soort pseudo-paradoxen te ontrafelen en de niet-statisticus wijs te maken in de verwarrende wereld van cijfers, gemiddelden, kansen en toeval.

Een relevant voorbeeld is dat van de zogenaamde kankerclusters. De auteurs gaan in op de zaak rond het Engelse dorpje Wisham, waar in 2003 de bewoners (20 huishoudens ) de plaatselijke GSM-mast naar beneden haalden, nadat er sinds het plaatsen van de mast bij negen van hen een tumor was vastgesteld. Onze hersenen zoeken verbanden en patronen ook waar er geen zijn. Mensen met een diagnose van kanker zijn niet mooi evenredig verspreid over het land en opeenhopingen (oftewel clusters) komen voor zonder dat dit is terug te voeren tot een specifieke oorzaak, zoals in dit geval de zendmast. Pak een handvol rijst, stellen de schrijvers voor in een poging wetenschap tot in de huiskamer te brengen, en gooi deze loodrecht naar omhoog. De manier waarop de rijst, eenmaal neergekomen, op de grond verspreid zal liggen, is geen perfect regelmatige verdeling. Sommige korrels liggen bij elkaar, hier en daar vallen gaten, en af en toe vind je een klein hoopje rijst: dat zijn de clusters.

Of flitspalen: werken ze of werken ze niet? Het boek geeft daarop geen antwoord maar zet wel vraagtekens bij de manier waarop nu met de beschikbare getallen wordt omgegaan. Vaak worden flitspalen op een bepaalde weg geplaatst nadat zich daar veel ongelukken hebben voorgedaan, en claimt de verantwoordelijke politicus succes wanneer het jaar daarna het aantal ongevallen is gedaald. Maar dat is te gemakkelijk. Het aantal ongevallen zal altijd variëren, het ene jaar meer, het andere jaar minder. En de kans dat er na een piekjaar een terugval komt, is groot, zoals ook de kans groot is dat je, na met een dobbelsteen een zes te hebben geworpen, bij de volgende poging lager zult uitkomen.

En zo is er nog veel meer : gemiddelde inkomens, toxische stoffen in onze omgeving, het bestaan van hobbits (jawel!), dopinggebruik in de sport, kwaliteitscontrole van de gezondheidszorg, de kans op recidiveren van geweldplegers en klimaatsverandering, om er maar een paar te noemen. Allemaal onderwerpen waar wij met behulp van cijfers iets nuttigs over proberen te zeggen. Alleen:

‘Things just won’t lie down and be counted under what politicians hoped would be one heading, but turn out to be complicated, manifold and infernally out of kilter.’

Populair-wetenschappelijk hoeft geen scheldwoord te zijn.½