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THE TIGER THAT ISN'T Seeing Through a World of Numbers
Numbers have become the all-powerful language of public argument. Too often, that power is abused and the numbers bamboozle. This book shows how to see straight through them - and how to seize the power for yourself. Public spending, health risks, environmental disasters, who is rich, who is poor, Aids or war deaths, pensions, teenage offenders, the best and worst schools and hospitals and immigration - life comes in numbers. The trick to seeing through them is strikingly simple. It is to apply something everyone has - the lessons of their own experience. Using vivid and everyday images and ideas, this book shows how close to hand insight and understanding can be, and how we can all use what is familiar to make sense of what is baffling. It is also a revelation - of how little the principles are understood even by many who claim to know better.
192 pages, Paperback
First published August 23, 2007
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Displaying 1 - 30 of 65 reviews
August 15, 2015
You don't have to be well versed in statistics to enjoy Blastland and Dilnot's book The Tiger That Isn't. Their aim is to teach their readers how to criticality examine and understand statistical claims in the news. Using a plethora of sometimes amusing, sometimes troubling examples they show how the government, the media, and special interest groups can misunderstand and misrepresent statistical analyses. I enjoyed this book and found it quite an eye opener. It's pretty scary how often statistical results are knowingly misrepresented for effect or gain. Just as often studies are incorrectly presented through ignorance.
Using simple arithmetic Bestland and Dilnot provide a few easy methods for detecting whether a statistical claim is outrageous or realistic. This book is perfect for people with just a basic mathematical background who want to learn to question the statistics they read. For those with more robust mathematical backgrounds many of the statistical concepts might be very simple, but I believe they might still enjoy the numerous examples of statistical studies being twisted to support various agendas.
July 18, 2020
There are three types of lies : lies, damned lies and statistics. Mark Twain- well maybe
Michael Blastland gives us a modern an up to date reminder of why we should not believe all the statistics we read. It is a rather topical book in the current COVID epidemic where we have seen a wholesale abuse of data. Michael runs through a number of very interesting examples of the abuse and misuse of data. It is well written and entertaining. My one criticism is that it focuses excessively on examples from England, and might have benefited from a more global perspective. Many of the examples from the British health service or from British politics are not very interesting to the non English reader. None the less it is well worth reading, and will probably warrant an extra chapter once the dust settles on COVID.
Michael Blastland gives us a modern an up to date reminder of why we should not believe all the statistics we read. It is a rather topical book in the current COVID epidemic where we have seen a wholesale abuse of data. Michael runs through a number of very interesting examples of the abuse and misuse of data. It is well written and entertaining. My one criticism is that it focuses excessively on examples from England, and might have benefited from a more global perspective. Many of the examples from the British health service or from British politics are not very interesting to the non English reader. None the less it is well worth reading, and will probably warrant an extra chapter once the dust settles on COVID.
July 5, 2023
"The Tiger That Isn't" was an interesting, quick read. It seems to me that it's most suitable for people that have no real prior statistical knowledge - journalists, e.g.. For political science or sociology students too if your statistics lecture doesn't give you enough non-technical input.
The book is well written with a decent british pint of homour, in a Penguin type of manner.
If you want to read a deeper/ slightly more technical book, i recommend David Spiegelhalter's "The Art of Statistics" (although it owes a lot to the book just discussed).
The book is well written with a decent british pint of homour, in a Penguin type of manner.
If you want to read a deeper/ slightly more technical book, i recommend David Spiegelhalter's "The Art of Statistics" (although it owes a lot to the book just discussed).
June 9, 2018
There are literally billions of books that do this kind of thing, not sure why I'm reading more, but this is OK, and kind of comforting in its examples which are all pre-2010 and the current hell in which statistics are just one of the things comprehensively melted by the jet fuel of Our Times.
May 3, 2014
I first read this book in 2008, not all that long after it was released, pretty much in one go on a long haul flight. I recently came across it again, remembered the pleasure I derived from it the first time round, and so gave it a re-read.
The Tiger That Isn’t provides a competent grounding in the very basics of statistical theory – risk, sampling, averages, etc – but does so in a way that is both relevant to daily life and, genuinely, laugh-out-loud funny. Blastland and Dilnot pick examples from many different spheres of life, but with a particular lean towards politics and the media, and explain the basic statistical errors underlying fallacious claims. They largely succeed in doing this in a lighthearted way, and attempt to equip readers with tools which might help them avoid similar mistakes in future.
One suggestion that I remembered from my first reading of this book is that any Government spending announcement is more easily interpreted if one divides the headline figure by 3bn, which gives an approximation of the spend per member of the population per week.
Of course, this book does not discuss statistical methods in great detail, and nor does it deal with some of the more complex statistical concepts. It does, however, give a good grounding in everyday statistics to those with a passing interest – I wish more journalists (and politicians) would give themselves a solid foundation of statistical understanding, and this is as good a place to start as any.
I very much enjoyed my re-read of this volume, and would happily recommend it to anyone with even a passing interest in the topic.
This review was originally published on my blog, at http://sjhoward.co.uk/archive/2014/02...
The Tiger That Isn’t provides a competent grounding in the very basics of statistical theory – risk, sampling, averages, etc – but does so in a way that is both relevant to daily life and, genuinely, laugh-out-loud funny. Blastland and Dilnot pick examples from many different spheres of life, but with a particular lean towards politics and the media, and explain the basic statistical errors underlying fallacious claims. They largely succeed in doing this in a lighthearted way, and attempt to equip readers with tools which might help them avoid similar mistakes in future.
One suggestion that I remembered from my first reading of this book is that any Government spending announcement is more easily interpreted if one divides the headline figure by 3bn, which gives an approximation of the spend per member of the population per week.
Of course, this book does not discuss statistical methods in great detail, and nor does it deal with some of the more complex statistical concepts. It does, however, give a good grounding in everyday statistics to those with a passing interest – I wish more journalists (and politicians) would give themselves a solid foundation of statistical understanding, and this is as good a place to start as any.
I very much enjoyed my re-read of this volume, and would happily recommend it to anyone with even a passing interest in the topic.
This review was originally published on my blog, at http://sjhoward.co.uk/archive/2014/02...
August 15, 2013
Dit boek heb ik al een paar keer gelezen en ik word er blij van. Het gaat over de statistische fouten die in de media (expres) gemaakt worden. Makkelijk geschreven en vól anekdotes die je op feestjes kan vertellen. En meteen ben je weer scherp over dingen als gemiddelden, regression to the main, correlatiefouten, operationalisaties, schattingen en nog veel meer.
December 10, 2024
Framing thy fearful symmetry
I bought this earlier this year and read it a week or so ago (coincidentally, just after "The Life Of Pi", which also featured a tiger). It promises to help make sense of claims involving numbers, to spot incorrect reasoning and to point out fallacies which have been promulgated by politicians, civil servants and journalists. To that end, it points out some handy things to remember when dealing with numbers - e.g. "A million seconds is about 11.5 days. A billion seconds is nearly 32 years" [p22] - and statistical concepts - e.g. "by chance" does not mean "without cause", or "statistics is an exercise in coping with, and trying to make sense of, uncertainty, not in producing certainty" [p122].
It also describes Pen's Parade: a vivid illustration of the uneven distribution of wealth, along with the difference between the mean and the median of a set of numbers (the former is given by adding all the numbers up and dividing by how many numbers are in the set, while the latter is the middle value if the numbers are arranged in increasing order). Pen visualised the economy as a parade of every person in it, arranged in order of income, beginning with the lowest. He further imagined that a person's height would be proportional to their income (so that those earning twice the average income would be twice the average height) and that we spectators would be of average height. What do we see? Surprisingly, not a series of people of steadily increasing height (which would imply a uniform distribution of income). Instead, the parade consists mostly of dwarves, (if the parade takes an hour to pass, the first person of average height doesn't arrive until about fifteen minutes before the end; recall that the person with the median income would appear after thirty minutes), with a tiny number of giants of incredible size at the conclusion of the parade.
It also presents several examples of misinterpretation of things like risk - for example [p111], when Cancer Research UK publicised the results of an Oxford study which determined that "a woman's risk of breast cancer increases by 6% for every alcoholic drink consumed on a daily basis", this was transformed by the BBC into "for every alcoholic drink a woman consumes, her risk of breast cancer increases by 6%" - which is quite different. The authors go on to point out that even interpreting the increase correctly is useless unless we know what the risk was originally. It turns out to be 9%, so an increase of 6% would be a new risk of 9.54%. This is for one drink (every single day); for two drinks (every single day) the risk would be about 10%, which would equate to one extra woman per hundred who would succumb to breast cancer.
This kind of careful deconstruction of the numbers is characteristic of this book, as they appeal to readers to question the conclusions which those politicians, civil servants and journalists apparently draw from them. I enjoyed reading it (and was pleased to come across a quotation from a collaborator on p166, a few days after having spoken with him), despite finding it somewhat heavy going in places.
Originally reviewed 9 October 2024
I bought this earlier this year and read it a week or so ago (coincidentally, just after "The Life Of Pi", which also featured a tiger). It promises to help make sense of claims involving numbers, to spot incorrect reasoning and to point out fallacies which have been promulgated by politicians, civil servants and journalists. To that end, it points out some handy things to remember when dealing with numbers - e.g. "A million seconds is about 11.5 days. A billion seconds is nearly 32 years" [p22] - and statistical concepts - e.g. "by chance" does not mean "without cause", or "statistics is an exercise in coping with, and trying to make sense of, uncertainty, not in producing certainty" [p122].
It also describes Pen's Parade: a vivid illustration of the uneven distribution of wealth, along with the difference between the mean and the median of a set of numbers (the former is given by adding all the numbers up and dividing by how many numbers are in the set, while the latter is the middle value if the numbers are arranged in increasing order). Pen visualised the economy as a parade of every person in it, arranged in order of income, beginning with the lowest. He further imagined that a person's height would be proportional to their income (so that those earning twice the average income would be twice the average height) and that we spectators would be of average height. What do we see? Surprisingly, not a series of people of steadily increasing height (which would imply a uniform distribution of income). Instead, the parade consists mostly of dwarves, (if the parade takes an hour to pass, the first person of average height doesn't arrive until about fifteen minutes before the end; recall that the person with the median income would appear after thirty minutes), with a tiny number of giants of incredible size at the conclusion of the parade.
It also presents several examples of misinterpretation of things like risk - for example [p111], when Cancer Research UK publicised the results of an Oxford study which determined that "a woman's risk of breast cancer increases by 6% for every alcoholic drink consumed on a daily basis", this was transformed by the BBC into "for every alcoholic drink a woman consumes, her risk of breast cancer increases by 6%" - which is quite different. The authors go on to point out that even interpreting the increase correctly is useless unless we know what the risk was originally. It turns out to be 9%, so an increase of 6% would be a new risk of 9.54%. This is for one drink (every single day); for two drinks (every single day) the risk would be about 10%, which would equate to one extra woman per hundred who would succumb to breast cancer.
This kind of careful deconstruction of the numbers is characteristic of this book, as they appeal to readers to question the conclusions which those politicians, civil servants and journalists apparently draw from them. I enjoyed reading it (and was pleased to come across a quotation from a collaborator on p166, a few days after having spoken with him), despite finding it somewhat heavy going in places.
Originally reviewed 9 October 2024
August 23, 2020
Pues es un libro que aunque no me dijera nada nuevo, la cantidad de ejemplos y la forma en la que esta escrita lo hizo un libro más que nada un poco entretenido y fácil y accesible para cualquier persona, pero nada grounbreaking de ninguna forma.
Incluye 12 lecciones sobre como a veces los datos que se utilizan son misenterpretados y ejemplo donde esto es exactamente lo que pasa.
1. Primero, empiezo con el size de los numeros que aunque suenen tan immeson o enanos, hay que bring esa cantidad al earth y repartiendolo por cada persona y semana, ver la immensidad de esos números, que ya no suenan tan impresionantes, especialmente cuando los periodicos hablan de goverment budgets.
2. Despues habla de como chance, puede dar la impresión de que un doctor es un serial killer cuando es simplemente chance, que aunque hay la percepcion de que algo random daría a patterns regulares, ese no es el caso.
3. Lo siguiente habla de como los números van siempre arriba y abajo, y cuando políticos dicen que algo a pasado gracias a ellos, igual no tienen tanta razón
4. Como el mean es usualmente usado para representar lo normal cuando puede ser facilmente skewed por los extremos y la media suele ser una representacion más accurate de lo normal.
5. De como los targets suelen ser muy abstractos y pueden enseñar que las situaciones en la NHS están mejorando, por ejemplo, cuando la verdad es que no todo se puede medir númericamente y esta rigidad con los números puede facilitar a la gente a ganar al sistema.
6. El riesgo de ser atacado por un tiburon o de morir de una enfermedad suele ser exagerado en los periodicos y tabloid news con tácticas como presentando un increase y no hablando del riesgo anterior.
7. Todas la estatísticas menos los bebes que nacen y sus nombres son recogidas de samples, y el número de mirepresentation que pueden arise de un sample que no representa proporcionalmente a la población que se está estudiando.
8. Algunos datos recolectados para llegar a ciertas conclusiones pueden ser de baja calidad.
9.La utilización de nuevo usada por periódicos de los outliers para conseguir el shock de los readers.
10. Lo que se cuenta, suele solo representar aquello que los investigadores an querido incluir bajado su definicion bien estrecha.
11. La comparación entre dos datos tiene que asegurar que los control factors se mantienen igual.
12. Correlation doesn´t cause causation y normalmente hay una tercera razón que explica la relación de los primeros dos factores
Incluye 12 lecciones sobre como a veces los datos que se utilizan son misenterpretados y ejemplo donde esto es exactamente lo que pasa.
1. Primero, empiezo con el size de los numeros que aunque suenen tan immeson o enanos, hay que bring esa cantidad al earth y repartiendolo por cada persona y semana, ver la immensidad de esos números, que ya no suenan tan impresionantes, especialmente cuando los periodicos hablan de goverment budgets.
2. Despues habla de como chance, puede dar la impresión de que un doctor es un serial killer cuando es simplemente chance, que aunque hay la percepcion de que algo random daría a patterns regulares, ese no es el caso.
3. Lo siguiente habla de como los números van siempre arriba y abajo, y cuando políticos dicen que algo a pasado gracias a ellos, igual no tienen tanta razón
4. Como el mean es usualmente usado para representar lo normal cuando puede ser facilmente skewed por los extremos y la media suele ser una representacion más accurate de lo normal.
5. De como los targets suelen ser muy abstractos y pueden enseñar que las situaciones en la NHS están mejorando, por ejemplo, cuando la verdad es que no todo se puede medir númericamente y esta rigidad con los números puede facilitar a la gente a ganar al sistema.
6. El riesgo de ser atacado por un tiburon o de morir de una enfermedad suele ser exagerado en los periodicos y tabloid news con tácticas como presentando un increase y no hablando del riesgo anterior.
7. Todas la estatísticas menos los bebes que nacen y sus nombres son recogidas de samples, y el número de mirepresentation que pueden arise de un sample que no representa proporcionalmente a la población que se está estudiando.
8. Algunos datos recolectados para llegar a ciertas conclusiones pueden ser de baja calidad.
9.La utilización de nuevo usada por periódicos de los outliers para conseguir el shock de los readers.
10. Lo que se cuenta, suele solo representar aquello que los investigadores an querido incluir bajado su definicion bien estrecha.
11. La comparación entre dos datos tiene que asegurar que los control factors se mantienen igual.
12. Correlation doesn´t cause causation y normalmente hay una tercera razón que explica la relación de los primeros dos factores
June 24, 2024
According to its authors: “Mathematics scares and depresses most of us, but politicians, journalists and everyone in power use numbers all the time to bamboozle us. It is liberating to understand when numbers are telling the truth or being used to lie.”
According to Steven Poole at the Guardian: “This very elegant book… constantly sparks “Aha!” moments as it interrogates the way numbers are handled and mishandled by politicians and the media.”
The Tiger that Isn’t isn’t just a book about statistics and how they are used to tell stories, it also provides the antidote to spin. It teaches you how to ask the questions that will cut through the rhetoric and explains how to use numbers to understand what is really going on.
Dilnot and Blastland discuss a multitude of statistical tricks and sleights of hand. They cover everything from averages to sampling and randomness to target setting. Numbers sound cold, hard and unequivocal, but they can be deceptive when taken out of context. The book is full of examples:
– Mrs Thatcher’s government changed the definition of “unemployed” twenty-three times during the 1980s.
– In the UK, almost everyone has more than the average number of feet.
– Should you allow yourself to be treated by the surgeon with the highest death rate in the country?
Blastland and Dilnot explain why Albert Einstein was right when he said, “Information is not knowledge.”
The book provides clear guidance about asking questions when people argue with numbers.
– What to do when presented with a large value.
– What to do when presented with a causal relationship.
– What to do when presented with a statistic.
– What to do when presented with performance against a numerical target.
The book is easy to understand and contains some fascinating stories. It will make you think twice the next time a politician or journalist tries to spin some statistics your way. You will also start to question the numbers bandied about in your organisation.
According to Steven Poole at the Guardian: “This very elegant book… constantly sparks “Aha!” moments as it interrogates the way numbers are handled and mishandled by politicians and the media.”
The Tiger that Isn’t isn’t just a book about statistics and how they are used to tell stories, it also provides the antidote to spin. It teaches you how to ask the questions that will cut through the rhetoric and explains how to use numbers to understand what is really going on.
Dilnot and Blastland discuss a multitude of statistical tricks and sleights of hand. They cover everything from averages to sampling and randomness to target setting. Numbers sound cold, hard and unequivocal, but they can be deceptive when taken out of context. The book is full of examples:
– Mrs Thatcher’s government changed the definition of “unemployed” twenty-three times during the 1980s.
– In the UK, almost everyone has more than the average number of feet.
– Should you allow yourself to be treated by the surgeon with the highest death rate in the country?
Blastland and Dilnot explain why Albert Einstein was right when he said, “Information is not knowledge.”
The book provides clear guidance about asking questions when people argue with numbers.
– What to do when presented with a large value.
– What to do when presented with a causal relationship.
– What to do when presented with a statistic.
– What to do when presented with performance against a numerical target.
The book is easy to understand and contains some fascinating stories. It will make you think twice the next time a politician or journalist tries to spin some statistics your way. You will also start to question the numbers bandied about in your organisation.
July 18, 2024
مش قادرة أحدد ان كان الكتاب ده أسهل من كتاب سان بلو " الكتاب الأكثر مبيعا على الإطلاق: كيف تقودنا الأرقام وتضللنا " اللي قرأته في نفس الموضوع، ولا عشان اتعرفت على الفكرة من الكتاب التاني فالتجربة هنا كانت اسرع واقل مفاجأة، لكن الاتنين أحلى من بعض للمهتمين بالإحصاء والتعامل مع مخادعات الأرقام، فيهم قصص مفيدة كتير وتوضيحات لأخطاء بنقع فيها كل يوم وبما اني كتبت بالتفصيل في الكتاب التاني عن الموضوع فهكتفي بانطباعي هنا عن بعض المواضيع..
في هنا حصر للأحداث في المملكة المتحدة، بنسبة كبيرة يعني لأن الكاتبين مقدمين برنامح عن موضوع الكتاب على راديو بي بي سي، ومن مميزات الكتاب ان في تفاصيل كويسة من خلال القصص بتسهل فهم القصة خصوصا في موضوعات التضليل في الطب والتعليم وهكذا..
الملاحظة التانية إنهم لفتوا الانتباه لكم كذب عن مستويات الرعاية الصحية والتعليم في اوروبا وأمريكا وان بيتم التلاعب فيها بشكل رهيب.. خلاني استغرب قد ايه بيتضحك علينا..
يعني مثلا قالوا ان من ضمن الرفاهية اللي بتروج ليها الحكومة في بريطانيا عن مستزى الطب هي ان السخص من حقه يختار افضل مستشفى يناسبه ويقدم له رعاية وثبت ان التحسينات بس كانت في مستويات أكل المطاعم اللي داخل المستشفى، ومساحات ركن السيارات..
ترجمة الكتاب جيدة جدا أفضل بكتير من ترجمة كتاب سان بلو
في هنا حصر للأحداث في المملكة المتحدة، بنسبة كبيرة يعني لأن الكاتبين مقدمين برنامح عن موضوع الكتاب على راديو بي بي سي، ومن مميزات الكتاب ان في تفاصيل كويسة من خلال القصص بتسهل فهم القصة خصوصا في موضوعات التضليل في الطب والتعليم وهكذا..
الملاحظة التانية إنهم لفتوا الانتباه لكم كذب عن مستويات الرعاية الصحية والتعليم في اوروبا وأمريكا وان بيتم التلاعب فيها بشكل رهيب.. خلاني استغرب قد ايه بيتضحك علينا..
يعني مثلا قالوا ان من ضمن الرفاهية اللي بتروج ليها الحكومة في بريطانيا عن مستزى الطب هي ان السخص من حقه يختار افضل مستشفى يناسبه ويقدم له رعاية وثبت ان التحسينات بس كانت في مستويات أكل المطاعم اللي داخل المستشفى، ومساحات ركن السيارات..
ترجمة الكتاب جيدة جدا أفضل بكتير من ترجمة كتاب سان بلو
April 1, 2023
كتاب يتكلم عن الإحصاء وطريقه الإحصاء واخطاء الإحصاء ونتائج الإحصاء. كتاب جدا جميل، يعطيك نظره وفكره عن الارقام اللي نقراها يوميا او نسمع عنها واستنباط المعنى لكل رقم في احصائيات مختلفه، هل الرقم كبير؟ هل تم الإحصاء بشكل سليم؟ هل الإحصاء شامل لكل المعلومات؟. بالأضافه، في هذا الكتاب تستوعب ان كثير من الدراسات والمقارنات تكون نتائجه غير صحيحه او فيها نسبه من الأخطاء والأرقام اشبه ما تكون أرقام وهميه. كثير من مستخدمين الارقام يستخدمونها لصالحهم (مدعومه بدراسات وإحصائيات لكن بالحقيقه نتائج هذي الدراسات والإحصائيات تكاد تكون مختلفه بفارق كبييير)
استفدت من هذا الكتاب في تحليل الارقام الخياليه اللي نشوفها ونسمع عنها بالاخبار. كنا دائما نقول ان الارقام الصحيحه والنسب المئويه ما عليها اي خلاف ولكن اكتشفت طريقه قرائتنا لها او استخدامنا إياها تكون خطأ بحد ذاتها ، بالتالي القيمه المعنويه للرقم في الدراسات او الابحاث او الإحصاء او المقارنات تختلف اختلاف ممكن يكون جدا كبير.
ملاحظة ايجابية:
الكتاب إلكتروني صفحاته ٢٠٠ تقريبا.
اقراه في جوالي ومعاي وين ما أروح.
ملاحظة سلبيه:
- كانت الترجمة من نبيل العدلي والمراجعة من هبة عبدالعزيز غانم (للآسف) في بعض الأخطاء اللغوية بالكتاب.
استفدت من هذا الكتاب في تحليل الارقام الخياليه اللي نشوفها ونسمع عنها بالاخبار. كنا دائما نقول ان الارقام الصحيحه والنسب المئويه ما عليها اي خلاف ولكن اكتشفت طريقه قرائتنا لها او استخدامنا إياها تكون خطأ بحد ذاتها ، بالتالي القيمه المعنويه للرقم في الدراسات او الابحاث او الإحصاء او المقارنات تختلف اختلاف ممكن يكون جدا كبير.
ملاحظة ايجابية:
الكتاب إلكتروني صفحاته ٢٠٠ تقريبا.
اقراه في جوالي ومعاي وين ما أروح.
ملاحظة سلبيه:
- كانت الترجمة من نبيل العدلي والمراجعة من هبة عبدالعزيز غانم (للآسف) في بعض الأخطاء اللغوية بالكتاب.
January 11, 2023
من حسن الحظ بدء قراءات 2023 بهذا الكتاب، فهو جسد بشكل متماسك كثيرا من الأفكار التي كانت تدور في رأسي دون أن أنجح في صياغتها على وجه من الدقة المدعمة بالأمثلة.
هو كتاب ممتاز في التعامل مع الأرقام والإحصاءات والمغالطات المضمنة فيها على نحو شبه دائم، أرى قراءته من الأمور الضرورية لأي مسؤول أو صحفي في زمننا هذا، وهو بالمناسبة متاح مجانا باللغة العربية عبر مؤسسة هنداوي.
المشكلة أن هذا الكتاب قد صدر قبل ما حدث في التعامل مع أزمة فيروس كورونا ومع ذلك يبدو أن كثيرين ممن قرؤوه على الأقل في بريطانيا لم يربحوا منه قناعات صلبة تقف في وجه الهيستريا التي عشناها جميعا.
ملاحظة أخيرة على الترجمة: كان الأفضل عند التعامل مع بعض الأرقام الكبيرة تجنب كتابتها بالأصفار الكثيرة التي يعسر على أصحاب النظر الضعيف أمثالي قراءتها، كان من الأولى أن تكتب بالحروف كلما أمكن كأن يقال 23 مليونا أو سبعة مليارات وهكذا.
هو كتاب ممتاز في التعامل مع الأرقام والإحصاءات والمغالطات المضمنة فيها على نحو شبه دائم، أرى قراءته من الأمور الضرورية لأي مسؤول أو صحفي في زمننا هذا، وهو بالمناسبة متاح مجانا باللغة العربية عبر مؤسسة هنداوي.
المشكلة أن هذا الكتاب قد صدر قبل ما حدث في التعامل مع أزمة فيروس كورونا ومع ذلك يبدو أن كثيرين ممن قرؤوه على الأقل في بريطانيا لم يربحوا منه قناعات صلبة تقف في وجه الهيستريا التي عشناها جميعا.
ملاحظة أخيرة على الترجمة: كان الأفضل عند التعامل مع بعض الأرقام الكبيرة تجنب كتابتها بالأصفار الكثيرة التي يعسر على أصحاب النظر الضعيف أمثالي قراءتها، كان من الأولى أن تكتب بالحروف كلما أمكن كأن يقال 23 مليونا أو سبعة مليارات وهكذا.
September 15, 2024
My maths teacher made me read this book, and it was a very interesting read. I loved the analogies and metaphors involved when discussing various potential holes in the gathering of statistics. The only thing I would say as a mainly romantasy reader, is that I could not get into it. It wasn't quite interesting enough to hook me, but I still wanted to continue reading just in case I found a particularly interesting example or surprising hole in one form of statistics or another. If you love maths and politics, read it 100%. But if you're like me and you're good at maths as a subject and in a test paper rather than interested in statistics found in the news, it's not worth the read.
October 21, 2025
In my small, single person dataset, it would be incorrect to say that "This book took me 2 months to read, which is longer than typical for its length. Therefore, this book was disinteresting and poorly written." as that would be a causation/correlation error. Instead, we may consider the confounders, such as how I only read the book on the subway, or how I started other books while reading this one.
Overall, interesting breadth of examples and clear succinct summary at the end. Blastland’s and Dilnot’s lay and witty writing let’s the personality in numbers shine through.
Overall, interesting breadth of examples and clear succinct summary at the end. Blastland’s and Dilnot’s lay and witty writing let’s the personality in numbers shine through.
January 22, 2018
Geeking out with this book about the value of statistics but the need to be cynical of data too.
Not so much academic as full of anecdotes (eg how the average pregnancy length/projected due data should be 283 days not 280), metaphors (how sampling is like trying to drink from a firehose), and incorrect assumptions (how less splatted hedgehogs on roads may not be a sign of fewer hedgehogs but less traffic).
Not so much academic as full of anecdotes (eg how the average pregnancy length/projected due data should be 283 days not 280), metaphors (how sampling is like trying to drink from a firehose), and incorrect assumptions (how less splatted hedgehogs on roads may not be a sign of fewer hedgehogs but less traffic).
September 25, 2020
I think the 3 stars that I gave is more testament to the fact that I've read a couple of others on the same topic, and therefore have stopped being "enlightened" by the content. For me, it's now more about getting a refresher every so often with new examples and/or and entertaining writing style, which unfortunately I didn't find in this one. Still a decent book on the topic, good coverage of the different data sleights that can be applied to numbers seen in the mass media and the like.
January 23, 2021
I’d actually give this more like 3.5 Stars. It’s a good and interesting book. At the same time it is a book about numbers and math, so, although the authors present the information well and give good examples and explanations, it is still a little dry. I read it along with a novel; I’d read ten pages a night before moving on to fiction.
February 7, 2018
A badly written collection of excellent ideas. The authors impart great clarity as to how numbers are to be UNDERSTOOD. A helpful guide in these data-crazy times. My gripe is that the authors try to be unnecessarily and excessively nformal at times.
March 10, 2022
Opened my eyes to how wrong we can be with numbers.
Hopefully, I will remember this and pause when I see the various statistics and claims which 'experts' and government bodies like to throw about without due consideration of what is really being measured.
Hopefully, I will remember this and pause when I see the various statistics and claims which 'experts' and government bodies like to throw about without due consideration of what is really being measured.
June 4, 2017
Excellently written accessible even for a doctor with very little brain - a lot of the examples and illustrations are around health - a great introduction to sceptical thinking about statistics.
May 1, 2018
Maths for the layman. Simple language, practical examples. Well demonstrated points.
February 9, 2020
Easy read from the presenter of More or Less (which I always enjoy). Clear examples and explanations - a great read for someone who thinks they don't understand numbers or is easily bamboozled.
June 30, 2021
Over 15 years old and therefore a lot of the examples are quite distant. Certainly reinforces the basics of being cynical and enquiring when numbers are quoted and conclusions are extracted.
January 15, 2022
Should be required reading for anyone who makes decisions that affect others. Our interpretation of what we are told is so personal and yet I doubt many people realise this.
May 26, 2022
Cool story bro needs more tigers
December 26, 2022
أفكار ليست صعبة ليست ذات عمق اقتصادي رهيب ويتم شرحها باستفاضه ممله
January 16, 2023
So insightful, everyone should read. So many things I had never thought about that now I can’t not see when it comes to media/news. Could be dry if you don’t like numbers but I loved it.
March 19, 2023
Math brings me great anxiety. This has helped clear some things up but not so much others. It is a good read tho
March 28, 2025
Illusion explained
December 23, 2015
This pre-Crash somewhat polemic introduction to the use and misuse of statistics in public policy and the media comes from the creators of the estimable and corrective Radio 4 Programme More or Less.
Since it was published, More or Less has been a rational thorn in the side of Government officials, campaigning NGOS and tabloid editors who misuse data knowing or unknowingly for their own purposes.
The book is a primer on or perhaps manifesto for sensible thinking about what numbers can and cannot do and we should worry if, eight years on, the basic lessons have not been learned by Government.
Every day shows us that the Press and the almost sociopathic NGOs have not learned any lessons at all. At least the two people authoring this book were standing up for intellectual integrity in 2007.
Unfortunately the book is written as if it was a leisurely radio broadcast, conversationally steering an unsatisfactory line between populism and the scientific method.
I wanted tighter editing and a less easy-going style with the space saved given over to more examples of public policy error and campaigning manipulation.
In the end, the style, like radio, makes the narrative a little forgettable. It does not stick in the mind as a set of techniques for critiquing public policy. Those techniques are what we really want.
Perhaps I am being unfair because a polemic may have been required in the dying days of the manipulative political culture constructed by New Labour. We have since moved on -though not as far as we could.
More or Less has, since then, created a very substantial body of work. It has developed a significant and educated listenership so perhaps it might not need to be written in quite this way today.
What struck me, however, was that the authors seemed terribly reluctant to stick the knife into the carcase of our political culture very deep. It was as if they did not want to burn their bridges.
What is needed now is something more brutal than this book. We need an investigation not of our ignorance but of the will to manipulate ignorance and the wider failure to educate us out of ignorance.
My reading of this book is not that people are stupid but that they are human, overwhelmed by data. They should be able to trust those they elect, give money to or who supply their information. They cannot.
The problem is only partly a matter of better education (in which the authors play their part). It is equally an issue of politics.
The public should not have to become statisticians to protect itself. The emphasis on us protecting ourselves is the wrong one - it is the elite, Government, NGO and media, that have to be brought to account.
Every time a Government or NGO or corporation or newspaper manipulates data to sell something - a policy, a cause, a product or a story - they should be called out. This book pulled its punches.
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