The Art of Statistics: How to Learn from Data by David Spiegelhalter (PDF)

Description

In this “important and comprehensive” guide to statistical thinking (New Yorker), discover how data literacy is changing the world and gives you a better understanding of life’s biggest problems. Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence — and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems — it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and — perhaps even more importantly — we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

User’s Reviews

Editorial Reviews: Review “An important and comprehensive new book”―Hannah Fry, The New Yorker”David Spiegelhalter’s The Art of Statistics shines a light on how we can use the ever-growing deluge of data to improve our understanding of the world…. The Art of Statistics will serve students well. And it will be a boon for journalists eager to use statistics responsibly — along with anyone who wants to approach research and its reportage with healthy skepticism.”―Evelyn Lamb, Nature”The Art of Statistics is alight with Spiegelhalter’s enthusiasm …. It leaves readers with a better handle on the ins and outs of data analysis, as well as a heightened awareness that, as Spiegelhalter writes, “Numbers may appear to be cold, hard facts, but … they need to be treated with delicacy.” ―Sciencenews”A book that crams in so much statistical information and nonetheless remains lucid and readable is highly improbable, and yet here it is. In an age of scientific clickbait, ‘big data’ and personalised medicine, this is a book that nearly everyone would benefit from reading”―Stuart Ritchie, The Spectator”This is an excellent book. Spiegelhalter is great at explaining difficult ideas…Yes, statistics can be difficult. But much less difficult if you read this book”―The Evening Standard (UK)”What David Spiegelhalter does here is provide a very thorough introductory grounding in statistics without making use of mathematical formulae. And it’s remarkable. Spiegelhalter is warm and encouraging — it’s a genuinely enjoyable read…. This book should be required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force.”―Popular Science”Do you trust headlines telling you…that bacon, ham and sausages carry the same cancer risk as cigarettes? No, nor do I. That is why we need a book like this that explains how such implausible nonsense arises in the first place. Written by a master of the subject…this book tells us to examine our assumptions. Bravo.”―Standpoint”Spiegelhalter goes beyond debunking numerical nonsense to deliver a largely mathematics-free but often formidable education on the vocabulary and techniques of statistical science…. An admirable corrective to fake news and sloppy thinking.”―Kirkus”A call to arms for greater societal data literacy…. Spiegelhalter’s work serves as a reminder that there are passionate, self-aware statisticians who can argue eloquently that their discipline is needed now more than ever.”―Financial Times”Like the fictional investigator Sherlock Holmes, Spiegelhalter takes readers on a trail to challenge methodology and stats thrown at us by the media and others. But where other authors have attempted this and failed, he is inventive and clever in picking the right examples that spark the reader’s interest to become active on their own.”―Engineering & Technology”What David Spiegelhalter does here is provide a very thorough introductory grounding in statistics without making use of mathematical formulae. And it’s remarkable. Spiegelhalter is warm and encouraging — it’s a genuinely enjoyable read…. This book should be required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force.”―Pop Science Books”In this wonderfully accessible introduction to modern statistics, David Spiegelhalter has created a worthy successor to classics such as Mooney’s Facts from Figures. Using many real examples, he introduces the methods and underlying concepts, showing the power and elegance of statistics for gaining understanding and for informing decision-making.”―David J. Hand, author of The Improbability Principle”David Spiegelhalter combines clarity of thinking with superb communication skills and a wealth of experience of applying statistics to everyday problems. The result is The Art of Statistics, a book that manages to be enjoyable as well as informative: an engaging introduction for the lay person who wants to gain a better understanding of statistics. Even those with expertise in statistics will find much within these pages to stimulate the mind and cast new light on familiar topics. A real tour de force which deserves to be widely read.”―Dorothy Bishop, professor of developmental neuropsychology and Wellcome Trust Principal Research Fellow in the Department of Experimental Psychology, University of Oxford”If I had to trust just one person to interrogate statistical data, I’d trust David Spiegelhalter. He is a master of the art. Here, he shows us how it’s done. The result is brilliant; nothing short of an essential guide to finding things out — delivered through a series of detective-like investigations of specific examples ranging from sexual behavior to murder. The technical essentials are also all here: from averages to infographics, algorithms and Bayesian statistics – both their power and their limitations. All this makes The Art of Statistics a first call for all those setting out on a career or study that involves working with data. But beyond that, it’s self-help for anyone with a serious desire to become a clued-up citizen in a world of numbers. If you want pat answers, or meat for your prejudices, go elsewhere. But if you want to develop the skills to see the world as it is, and to tell it how it is — honestly and seriously — this is the book.”―Michael Blastland, co-author of The Tiger That Isn’t: Seeing Through a World of Numbers”David Spiegelhalter is probably the greatest living statistical communicator; more than that, he’s one of the great communicators in any field. This marvelous book will transform your relationship with the numbers that swirl all around us. Read it and learn. I did.”―Tim Harford, author of The Undercover Economist”Some (including Einstein) define genius as the art of taking something complex and making it simple. In this equation-free, all-encompassing, and totally-understandable-by-anyone introduction to the ideas, tools, and practice of statistics, Spiegelhalter meets that definition. This book is perfect for anyone who has wanted to learn statistics but felt overwhelmed by complicated mathematical equations.”―Scott Page, author of The Model Thinker About the Author David Spiegelhalter is a British statistician and Chair of the Winton Centre for Risk and Evidence Communication in the Statistical Laboratory at the University of Cambridge. He was also elected as President of the Royal Statistical Society for 2017-18. In addition to presenting documentaries on BBC4, he has appeared on Infinite Monkey Cage, BBC Horizon, and the Life Scientific, and he has been a guest columnist in the Times, Guardian, and New Scientist. Spiegelhalter was knighted for his services to statistics in 2014. He lives in Cambridge, UK.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐I very much enjoyed reading this book- cover to cover- the 380 pages of content- and then the additional glossary which in itself is a great resource. This book is not the “nuts and bolts” of how you do the standard statistical tests. This book assumes you have looked at other resources for the formulas.What this book does better than ANYTHING I have ever come across (and I have come across a lot of books on statistics and analytics over the years) is to get you to understand-really understand– the key concepts, principles, assumptions and even mindsets that underlie the use of the basic– and foundational– statistical concepts.Prof Spiegelhalter has a remarkable ability to write and tell stories in clear and simple ways that get you to understand the essence of the principles. He walks you through many real and relevant examples so you understand the essentials of the underlying math models and mental models, and in parallel, that you also understand common mistakes and misconceptions.Some of you might say– why do I need to visit– or more likely- revisit these basic– and ubiquitously applied- principles and methods? After all, isn’t this becoming increasingly automated? Can’t I just “trust” the outputs of my AI-enabled analytic systems?Exactly because the use of statistics has become so widespread, so deeply embedded in so many analytics and prediction systems– it could never be more important than now to understand why people (and the models and systems they design) SO OFTEN misunderstand and misapply the basics. And these basics are foundational. They underlie so many aspects of modern analytics— and even modern AI-based systems ultimately end up using these basics.All I can say is— even though I have a MSc in Stats from Carnegie Mellon (1981), and have been involved with the use of data, statistics, analytics, and AI applications for decades– I found Prof Spiegelhalter’s way of walking a reader through the essentials of statistical thinking to be a joy to read. It has tremendously helped me to clarify my own understanding and mental models per statistical basics.This book truly works for people at ANY level. If you are just beginning with statistics- and you know the formulas but you still don’t have the intuitions and insights- please read this book.If you work with stats on a regular basis— EITHER because you are part of a team that uses statistical methods in your work products— OR— you regularly REVIEW work products that provide the results of analytic models– You will find this book invaluable.And if you have to get other people to understand how to apply and how to NOT misapply basic statistical principles- this book is a hugely useful resource.Thank you Prof Spiegelhalter for producing this work. It is so easy to read. So easy to understand. And at the same time, so insightful, and so thoughtful– in so many practical ways.

⭐For those who want to better understand statistics withouth getting bogged down by a super-dry college textbook or similar work, this is a good alternative. The content is general enough that it can be applicable to a range of studies and topics. There are decent amount of visuals to go with the explanations as well, and can serve as a good reference when you need a refresher. It doesn’t stand in for a mid-level or advanced Stats class but for everyone else it’s a useful way to improve your understanding of statistical principles.

⭐The author is a very good explainer who fills in background and makes an important tool seem easy. I recommend this book to my university Analytics students.

⭐Quite enjoyable and not so dry to read for a statistical book. Almost easy to understand but not that easy…Some point require more elaboration, for example in chapter 10, page 352:”the fact that this 95% interval include 0 is logically equivalent to the point estimate (-3000) being less than 2 standard errors from 0, meaning the change is not significantly different from 0″- i’m totally lost here, i failed understand what the author trying to tell. If there is any material in previous chapter that could help in understanding this sentence, the author should do some kind of revision before dive in. Otherwise, further elaboration is needed.”A two sided P-value is less than 0.05 if the 95% confidence interval does not include the null hypothesis (generally 0)” – Seem like a lot of info, but at the same time abstracted in statistical language. Totally lost. can use a bit more explanation in layman term about this “p-Value” in the context of “two sided”, “95% confidence interval”, “null hypothesis” combination of terminology. I am no total layman in statistic but these term and definition always confuses me, especially now it comes togetherRegards

⭐Good book to understand statistics and answer questions that are common. It teaches you and molds your critical thinking so that you are less susceptible to lying with statistics and you are also able to understand data for yourself. I am a Mathematics Ph.D. student and this was a very good read.It should, hands down, be a requirement to read in high school.

⭐The author brings up many important methods in statistics, but only describes what they do rather than how they are done. You thus get a very good sense of the terminology of stats, but not much understanding of stats itself. The pattern he follows throughout the book is to bring up a statistical term, point to its definition in the glossary (which is extensive), then describe what the method is and is not used for, citing several examples. This is a rather lazy approach as he never actually explains the mechanics of the method.

⭐Many books have sought to explain basic concepts of statistics with minimal mathematics, but this book will surely be the “gold standard” for the 2020s. It combines careful exposition with an impressive collection of interesting real data examples. In part it treats the usual textbook basics — summary statistics, graphics, randomized controlled experiments, sampling, regression, statistical significance, Bayes. Then modern ideas such as algorithmic prediction (and one of my personal favorites, Brier scores). It puts substantial emphasis on “when things can go wrong” and “how we can do statistics better” (both chapter titles) and on journalistic communication of statistical ideas.This book should be a required accompaniment to a traditional math-oriented first college course.[The 448 pages in the hardback version is rather misleading — there are few words per page]

⭐When I am not writing witty and informative reviews on Amazon my day job is as a Government statistician. Therefore when offered the opportunity to read this book I thought it would be useful for me to do so. And I do believe it is helping me in my work. I am thinking more about how best to present my statistics and what analytical techniques I could use too. So this book works from that perspective.This book takes real world questions and shows you how they’ve been answered introducing various statistical techniques as it does so. It does this whilst aiming to avoid “getting embroiled in technical details”. The questions picked are quite interesting subjects like “why do old men have big ears?”, “how many trees are there in this planet?” (an estimated 3.04 trillion if you must know) or what height will a son/daughter be given their parents’ heights and so on with some of the questions being based on work the author has been involved in during his career. Relating the problems to real life helps make the text appeal not only to statisticians (to which this book is dedicated) but also to non-technical readers “who want to be more informed about the statistics they encounter both in their work and in everyday life.”Some of this is not new stuff, e.g. early bits on presentation of data such as 3D pie charts not being useful for comparing proportions. But the book does get more involved as you work through it getting deeper in statistical techniques making it harder to understand and requiring more concentration, and the author is aware of this, for example asking if it is “all clear? If it isn’t then please be reassured that you have joined generations of baffled students”. Also the conclusion congratulates you for getting to the end.Useful stuff in here for me was the chapter on regression (which is what I use more commonly than much of the rest), and the last couple of chapters after the hard stuff were good reading too, showing bad examples and good examples of statistics from journals and the like and explaining why (offering learning points).Technical stuff is relegated to the technical glossary so this book is readable (which is good for a book about statistics), although still hard in places. For my work it has been useful and I’m glad I read it and have it for future reference.

⭐For my sins I was forced to study Statistics as an undergraduate in engineering and later doing a business management diploma. In both courses I was confronted with textbooks that contained a lot of mathematics and equations. And the courses consisted of recipes, to dive into the books and use the formulas and tables to solve a given situation. Quite frankly, I emerged none the wiser despite all the notes, lectures and discussions.After reading a positive review of this book in the UK edition of the Spectator I bought a copy via Amazon. I am so glad I did, for it explained to me what I have been missing in Statistics all my working life, which is now past. Using just plain words in a style that is not talking down to the reader, David ‘Mirrorholder’, guided me through the beautiful world of statistics. It is evident that not only did David master statistics, but had such an insight, that he could teach others as a master of his subject. I am so glad that did put pen to paper.However, I do have a comment about the print quality of the book. My copy was printed and bound in Britain. The quality control was not enough. The meandering right hand margin that ranged from 16 to 11mm (I think the objective was a 15mm wide margin) was most distracting.

⭐The context of the book is established immediately with real-world examples (eg. Harold Shipman, bacon-eating and bowel cancer risk). The author moves judiciously between key concepts without drowning the reader in complexity. Importantly he has heeded Prof Stephen Hawkins – no formulas in the main text (they’re hiding in the appendix).After nearly 25 years of reading research papers as a Chartered Physiotherapist and having done an MSc in Health Services Research, this is undoubtedly the textbook I wish I had as an undergraduate.Starting with the ‘why’ of statistics, the rationale and methodology of stats becomes instantly clear to all. Easy to read, candid about his own difficulties (eg. labelling ‘excess deaths’ during Bristol Heart Scandal), Sir David Spiegelhalter has written a modern classic.Statistical and risk literacy should be intrinsic to all of us; learning to drive, ride a bike, cooking etc are effortlessly pursuits. Invest in this text and you are committing to freedom from statistical ignorance. Buy 2 and gift a friend.

⭐Whilst many popular science books simply explain WHY a subject is interesting, and tell stories around it, this book actually explains HOW statistics work.The reason this is such a rare thing is that there simply aren’t many people who can combine a world-leading scientific mind with storytelling skill and writing clarity. David Spiegelhalter’s varied career means that he’s been on the inside of so many fascinating statistical detective stories, from how it’s possible to spot a serial killer like Harold Shipman to analysing who lived and died during the Titanic disaster, and he uses these real life examples to lift the veil on what many people think of as the dark art of statistics. By the end of it there won’t be many readers who haven’t had several ‘lightbulb moments’ as they finally realise what their school teachers had clumsily tried to explain in turgid mathematical language – much easier in fluent, readable English!From A-level science students up to practising legal, medical, financial, economic and science professionals, it should be required reading on many a syllabus and reading-list – but don’t that let you think it’s a hard read. The charmingly readable style, footnotes that make you smile, and stories that engross, make this book a pleasure to spend time with.

⭐Though a little more complicated than I’d anticipated it would be, I found The Art of Statistics an interesting read, with numerous examples that were easy to relate to. The beginning, in particular, was highly informative with the explanation of ‘relative risk’ in relation to getting bowel cancer and the eating processed meat. This was explained really well by the author. But a couple more chapters in I found myself getting lost in the text. In addition, I would have also liked to see more information surrounding IQ and the many controversies associated with it. All I could find was a paragraph or two on Cyril Burt in the final chapter: How Things Go Wrong.The Art of Statistics reminded me somewhat of Ben Goldacre’s book: Bad Science. However, I found John Spiegelhalter text less accessible, probably because statistics (like maths) is generally a more difficult and confusing subject to write about, even when statisticians like Spiegelhalter do a remarkable job in writing as clearly and entertainingly as they do.I hope you find my review helpful.

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