A Field Guide to Lies and Statistics: A Neuroscientist on How to Make Sense of a Complex World

by Daniel J. Levitin

A guide to critical thinking in the 'post-truth' era, from the author of Sunday Times best-seller The Organized Mind

We live in a world of information overload. Facts and figures on absolutely everything are at our fingertips, but are too often biased, distorted, or outright lies. From unemployment figures to voting polls, IQ tests to divorce rates, we're bombarded by seemingly plausible statistics on how people live and what they think. Daniel Levitin teaches us how to effectively ask can we really know that? And how do they know that?

In this eye-opening, accessible guide filled with fascinating examples and practical takeaways, acclaimed neuroscientist Daniel Levitin shows us how learning to understand statistics will enable you to make better, smarter judgements on the world around you.

Genres: Nonfiction, Psychology, Science, Self Help, Politics, Sociology, Philosophy

266 pages, Kindle Edition

First published September 6, 2016

About the author

Daniel J. Levitin runs the Laboratory for Musical Perception, Cognition and Expertise at McGill University, where he holds the Bell Chair in the Psychology of Electronic Communication. Before becoming a neuroscientist, he worked as a session musician, sound engineer and record producer. He has written extensively both in scientific journals and music trade magazines such as Grammy and Billboard.

http://daniellevitin.com/levitinlab/L...

http://daniellevitin.com/publicpage/b...

Reviews

[Taryn · Rating 4 out of 5]

The most important component of the best critical thinking that is lacking in our society today is humility. It is a simple yet profound notion: If we realize we don’t know everything, we can learn. If we think we know everything, learning is impossible.

Who knew a book about numbers could be so entertaining? Weaponized Lies is written for the average person, those of us who aren't statisticians or scientists. It introduces fundamental critical thinking skills that will assist the reader in making logical decisions and analyzing claims made in the news. The spread of misinformation is not a new problem, but the internet has made it more pervasive. Some people and publications are more likely to be right than others, but no one is infallible. Bad information can be spread by people with an agenda or people who don't know any better. Regardless of motive, it's our job to think critically about information before we spread it or form opinions. By knowing what questions to ask, we can better assess the validity of claims. Levitin reminds us to be critical of information that confirms our biases too. I liked his method of asking the reader to question a previous statement in the book. It reminded me to remain alert and critical, even of Levitin's claims.

Critical thinking doesn’t mean we disparage everything; it means that we try to distinguish between claims with evidence and those without.

This edition is a repackaging of A Field Guide to Lies (pub. 9/6/16). The biggest (only?) difference is the introduction. In the updated introduction, Levitin argues that euphemisms, such as "fake news" or "extreme views," are doing a disservice to us all. It makes falsehoods sound less insidious than they are. False statements should be called what they actually are--lies.

This book is divided into three sections:

EVALUATING NUMBERS

Biases, inaccuracies, and honest mistakes can enter at any stage. Part of evaluating claims includes asking the questions “Can we really know that?” and “How do they know that?”

Numbers seem so objective and definitive, but they shouldn't be taken at face value. Statistics and infographics can be manipulated to lead you to a conclusion that doesn't hold up upon closer look. Sometimes our basic knowledge of the world can weed out the bad information immediately, but other times the deception is more obscured. We should always question how the numbers were collected and interpreted. Visual representations of statistics make a powerful impact and most people only give them a passing glance. Levitin explains the methods used to deceive with infographics. He uses real-world examples to reinforce the points. One example shown is the misleading chart shown at the Planned Parenthood hearing in 2015.

What is the likelihood of something occurring or being true? Probability gives us a much broader view than anecdotes and helps us make better decisions. Make sure you understand the "Probabilities" chapter, especially Bayesian probability, because it comes up in other chapters!  I was especially interested in probability in the medical industry, because understanding how probability works can make you a more empowered patient. If you get a positive result on a mammogram, what is the actual chance of having breast cancer? Under 10%, because the disease is relatively rare and the test is not perfect. There are also times when doctors have recommended unnecessary, intrusive operations based on faulty understanding of probability.

EVALUATING WORDS

This section includes tools to evaluate the information we encounter every day. We depend on experts to provide information, but does everything they say hold the same weight? No! For example, just because someone is world-renowned neurosurgeon* doesn't make them an expert in other fields, even other medical fields. Sometimes experts engage in speculation like the rest of us and it's important to be able to differentiate between opinions and evidenced-based claims. Levitin also lists the telltale signs of bias or deception. He explains different techniques used to deceive people, such as burying fallacious arguments in a cluster of facts. Does a website's claims to reveal "truth" actually indicate the opposite? Before we blindly accept a claim, we should also ask if there are any alternative explanations that weren't considered or revealed.

EVALUATING THE WORLD

The inner workings of the scientific community are a mystery to many and charlatans take advantage of this. In this section, Levitin explains the scientific method and the rigorous process through which scientists come to a consensus. He addresses the myths about science: (1) scientists never disagree and (2) a single experiment tells us all we need to know. He also explains common logical fallacies, so that we can better evaluate scientific claims. The autism/vaccines controversy is used to illustrate four logical fallacies in action.

The information presented in this book is not just helpful for evaluating the news. Bayesian thinking can help with a legal defense, making an important medical decision, or even evaluating salesperson's claims. The last chapter includes four case studies that apply the previous lessons in critical thinking to the real world. My favorite of the four was Levitin's personal story about his dog's illness. He and his wife were able to logically think through every option and choose the path that was best for their dog. They were able to be a peace knowing they had done everything they could for their dog, while also causing the least harm.

There are not two sides to a story when one side is a lie. .... Two sides to a story exist when evidence exists on both sides of a position. Then, reasonable people may disagree about how to weigh that evidence, and what conclusion to form from it. Everyone, of course, is entitled to their own opinion. But they are not entitled to their own facts. Lies are an absence of facts and, in many cases, a direct contradiction of them.

My only complaint is the "Numbers" chapter felt more fleshed out than the "Words" and "World" chapters. The last two sections went so fast and I was so disappointed when the content ended 2/3s of the way through. I wasn't ready for it to end yet! Maybe that's more of a compliment than a complaint! The remainder of the pages are filled with a glossary, supporting documentation, and an index.

We’re far better off knowing a moderate number of things with certainty than a large number of things that might not be so.

Weaponized Lies is about understanding the limits of our knowledge and not being ashamed to admit that we don't know everything. This book encourages people to think scientifically and suppress the temptation to automatically discount dissenting evidence. It's easy to submit to lazy thinking when we're bombarded with so much information and we're so busy with our everyday lives. None of us are logically perfect human beings, so it's important to be aware of our flaws.  This book is an excellent refresher course in thinking critically. It's helped me better articulate why I find some information manipulative or misleading. The best part of the book is that it gave me an upper hand in an ongoing argument with my husband (he was essentially "truncating the y-axis" to make a misleading point). Thanks, Daniel Levitin! ;D

NOTES:
* I used a neurosurgeon as an example because of Ben Carson's recent claims about memory: Washington Post, Wired.
* I read this book around the same time I watched Denial, a movie about a woman who was sued by a Holocaust denier for libel (a real-life case: Irving v Penguin Books). In the movie, the woman is frustrated with the defense's refusal to allow witness testimony and the lawyer's heartless questions. The defense maintains that they need to prove the case more objectively if they're going to win in a definitive way. Richard Rampton:"They're a strange thing, consciences. Trouble is, what feels best isn't necessarily what works best."
* Purple America Has All But Disappeared: This article on FiveThirtyEight terrified me more than anything else I've read recently: "In an increasing number of communities .... an entire generation of youth will grow up without much exposure to alternative political points of view. If you think our political climate is toxic now, think for a moment about how nasty politics could be 20 or 30 years from now."
* "The longer I live, the more I read, the more patiently I think, and the more anxiously I inquire, the less I seem to know...Do justly. Love mercy. Walk humbly. This is enough.” - John Adams
*Popular comic about the science news cycle.
*Important concepts to remember: belief perseverance ("once we form a belief or accept a claim, it's very hard for us to let go, even in the face of overwhelming evidence and scientific proof to the contrary") & perception of risk ("overestimating the relative risks of things that receive media attention")


__________________
I received this book for free from Netgalley and PENGUIN GROUP Dutton. This does not affect my opinion of the book or the content of my review. The publication date is March 7, 2017.

[Trish · Rating 4 out of 5]

Oh, boy, I wish every one of my fellow citizens had the information shared in this book as part of their reading regime. On one hand, it would make it much harder to convince people with statistics. On the other hand, it would be much harder to convince people with statistics. Come to think of it, I think nowadays most people mistrust statistics, unless the statistics back up their own opinion.

How many times I received end-of-quarter reports from some mutual fund company showing showing growth and profits exceeding other companies’ but their graphs do not have the axes on their bar charts or line graphs labelled. Even one so discrepant in the moneymaking arts as I know this for a sham report.

Levitin does a couple of things in this book: he describes common ways to use statistics to disguise facts. He points out common errors the best-intentioned of us make (like doctors determining probabilities in positive cancer screens) and leads us to the way to find answers. He demystifies “expert testimony” by pointing out that expertise is typically narrow.

Donald Trump features in this book, both quoted directly and by implication:

“Truth is the default position and we assume others are being truthful with us. An old joke goes, “How do you know that some is lying to you? Because they begin with the phrase to be perfectly honest. Honest people do not need to preface their remarks this way.”

In the last third of the book, Levitin runs through how to think straight: deduction and induction, logical fallacies, framing risk, and belief perseverance, ending with a separate chapter on Bayesian probability. Finally, he gives four case studies to see if you managed to understand what he’d been telling you all along. He ends with a physicist’s explanation of new ideas and what we really don’t know for sure.

Levitin is very good. The material in his book parallels an earlier book I’d reviewed, Psy-Q by Ben Ambridge, which takes a fun look at the ways we can deceive or stun our friends. And truthfully (?!), I found Ambridge's explanation of Bayesian probabilities a little more understandable and applicable. But if you are like me, you need to review those proofs again and again every which way before you can explain it yourself. Psy-Q is a Penguin Paperback Original.

Both these books would be very useful for high school or college students or educators. These experts (now I wonder if I can use that term ever again) try to make it easy for us whose expertise lies elsewhere. It seems that most Americans may have learned only half of what they needed to from this book, so learning what we didn’t the first time around will be useful for the rest of our lives.

On my blog is a short video of Levitin explaining logical fallacy which will give you some idea of the audience to whom he is speaking.

[Esil · Rating 4 out of 5]

If someone told me I would read a book about numbers and enjoy it as much as a good novel, I suspect I would snort with laughter. Not that I'm number phobic or a math hater, but reading about numbers seems like an awfully dull way to spend precious reading time. But Trish's review of A field Guide to Lies piqued my interest, so I decided to give it a try. And, in fairness, the title doesn't suggest that this is mostly a book about numbers. But it didn't make for dull reading. In a very matter of fact manner -- almost conversational -- Daniel Levitin walked me through different ways numbers and various forms of logic can be presented to look like facts for the purpose of manipulating opinions. His focus wasn't just on numbers, but the first half was very much focused on numbers while the second half was focused on word use and logical reasoning. It wasn't all news to me, but it was a good crisp survey and reminder. A Field Guide to Lies is definitely a good read for anyone who wants to approach news and information with a heavy dose of informed scepticism. In fact, it should really be required reading for all high school students -- not to mention all supporters of a particularly troublesome candidate in the upcoming election. Thank you to Netgalley and the publisher for an opportunity to read an advance copy.

[Jim · Rating 5 out of 5]

This is a book about how to spot problems with the facts you encounter, problems that may lead you to draw the wrong conclusions - critical skills that we need today since we're blasted with information in a society based on conspicuous consumption. Everyone wants our support or to sell us something & many are skilled at leveraging our inherent flaws in reasoning to this end. Reading this should be a prerequisite for posting on Facebook.

The flaws inherent in our reasoning are manifold. We're a story-loving species & try to find patterns in everything. Both of these are methods for simplifying the reasoning process by giving us hooks on which to hang all the data. We tend toward beliefs, often snap judgements based on previous experience. Once we believe in something, it is much harder to shake our thinking process into a different pattern. A newspaper headline can be a complete lie & shown so in the story that follows, but people remember the lie.

The book is broken into 3 sections. Each teaches methods for evaluating data & then contains real world examples, many taken from the current press.
Evaluating Numbers: starts off with a quote attributed to Mark Twain It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.
- Plausibility: There are lies, damn lies, & statistics, so the latter are a conundrum today. We're aware they can be used to lie convincingly, but they look so good to us. What we fail to consider is how they are figured & he gives some great examples of common errors in them, probability, & percentages.
- Fun With Averages: Summary statistics (the mean, median, & mode) are all useful IF they are used correctly. They can be downright deceiving if used incorrectly, though. The mean (what we usually think of as the 'average') is very sensitive to outliers while the median & mode are far less so. Again, he does a great job of putting this into real world examples of when each should be used, when avoided, & what we should watch for.
- Axis Shenanigans: Graphs are another great way to condense information in a way that makes more sense, but they can also easily be misleading by not labeling or creatively labeling the axes.
- Hijinks With How Numbers Are Reported: This section builds on the preceding sections to show how the underlying numbers can be manipulated & why it is often profitable to do so. He also mentions the fallacy of correlation versus causation, a very common trap.
- How Numbers Are Collected:"Just because there’s a number on it, it doesn’t mean that the number was arrived at properly." Wow. Again, great examples.
- Probabilities allow us to quantify future events and are an important aid to rational decision making. Without them, we can become seduced by anecdotes and stories. While Levitin does a great job of simplifying it, there are some terms that I needed to get very comfortable with. This is the main section where the text really helps since he gets into Fourfold tables which help make sense of the actual odds. This is not always intuitive. In fact, our brains are wired to see them incorrectly much of the time. The rest of the book refers back to this section regularly, so it's important to understand it.
Classic probability is what we typically think of, but it is based on symmetry & equal likelihood such in the case of a coin toss. All the possibilities are known & discreet, but this is often not the case in real world problems such as how well a drug works, AKA Frequentist Probability. There is also Subjective Probability, such as when someone expresses an opinion on the likelihood of a future event. To confuse the issue further, we often combine them. We also need to consider conditional probability when an event is informed by another event (e.g., most car accidents happen during rush hour) & remember that these do not work backward (Just because it is rush hour does not mean you are likely be in an accident if another condition changes, such as not driving.) but we often forget the conditions & think that way.

Evaluating Words: Language is slippery & defines how we think about things. Half truths are often the worst lies.
- How Do We Know? We rely on experts, certifications, licenses, encyclopedias, and textbooks. AKA, secondhand knowledge, so we need to evaluate the the source & the claims. Who is the source & how likely is it that they're right? Experts can be wrong, they're just less likely to be IN THEIR AREA OF EXPERTISE (next section) than a random person. If the claim is a good one, we should be able to evaluate the evidence & it should be well documented. The content of footnotes are especially important & should be fully explored.
- Identifying Expertise: People are generally only experts in a narrow field, especially today when everything is so complicated. My doctor's opinion on what ails my car shouldn't weigh as heavily as my mechanic's, but we're often swayed by degrees or popularity. Levitin outlines some great ways to identify snow jobs including looking at the URL domain & other handy tips for using the Internet wisely & avoiding common terminology pitfalls.
- Overlooked, Undervalued Alternative Explanations: This goes back to our beliefs & love of stories. When we're given a likely story, it's often difficult to think of another, but the preceding sections have given us great tools for spotting inaccurate statistics/probabilities, missing factors such as a control group, &/or cherry-picked data.
-CounterKnowledge...is misinformation packaged to look like fact and that some critical mass of people have begun to believe. Generally conspiracy theories & pseudoscience. They often rely on open questions & anomalies which are then whipped into a likely story.
“If you thought that science was certain - well, that is just an error on your part.” - Richard Feynman
"The whole problem with the world is that fools and fanatics are always so certain of themselves, but wiser people so full of doubts.” – Bertrand Russell

Evaluating the World: deals with critical thinking overall & there is some repetition of previous material, but here he pulls all the skills he's outlined together & shows them in a variety of situations.
How Science Works: He explains deduction & induction in scientific reasoning, where & how each should be used. Again, there are several excellent real-world examples & common pitfalls outlined, such as the reversal of logical statements.
Logical Fallacies: Correlation confused with causation comes up again along with common framing & prior belief issues.
Knowing What You Don't Know“There are things we know, things we are aware that we do not know, and some things we aren’t even aware that we don’t know.” There’s a fourth possibility, of course—things we know that we aren’t aware we know. It seems a bit confusing at first read, but read it over a bit & it makes perfect sense. Evaluating our own knowledge is really important & sometimes that means digging back into the foundations of that knowledge & laying out the problem properly. He does a great job of sorting it all out.
Bayesian Thinking in Science & Court: Unlikely claims require more proof than likely ones, but this relies on understanding probability properly & that's something our court system often gets wrong. It's so well known that it is called The Prosecutor's Fallacy.
Four Case Studies are great examples of weighing probabilities in real world situations. In the first, he decided on how to handle cancer in his dog. This book is worth reading for this one example alone.

There is a great conclusion to sum it up. In the print version, there is also an appendix that outlines & applies Baye's Rule, & a glossary. While this is very well read & great as an audio book for the most part, I'd suggest getting a text copy since there are some tables and logic equations that were helpful to look at.

I highly recommend this to everyone. If my kids were still in the house, I'd make it required reading & I'd test them on it. We're deluged with information constantly. This is a wonderful book on how to evaluate & make sense out of the flood.

[Andy · Rating 1 out of 5]

One of the most dangerous bits of confusion out there is the idea that "we live longer". I was very happy that Levitin addresses this early on (p.20), explaining that AVERAGE life expectancy is up a lot mainly because children don't die, not because there used to be no old people. 4* at that point. :-)

So why 1* for the book? Because on p.175, he makes an argument based on the statement that "people are living longer." For crying out loud, did he not read his own @#$%^& book?!

There's a bigger population of old people in America. That's true, but not because we all live to 100 now. It's because: 1. Fewer kids die (see above) and 2. People have fewer kids (so as a % more of the populace is old) and 3. The total population is bigger. Life expectancy at age 80 has barely changed (something you can verify even on the commercial website Levitin uses as a reference).

I get it that it's hard to think in terms of averages and populations. Unfortunately what this shambolic example illustrates is the utter hopelessness of Levitin's central premise, i.e. trying to teach the entire population to think critically/scientifically/statistically. And anyway, that premise is just not fair. There are gatekeepers of information, like professional writers, book reviewers, editors and such who do NEED to know this stuff if they're going to talk about it; it's their responsibility. It matters. Oy.

Better books for assorted audiences:
How to Lie with Statistics
Clinical Epidemiology: The Essentials
Bad Science

[David · Rating 4 out of 5]

A good mix of Nate Silver's The Signal and the Noise: Why So Many Predictions Fail - But Some Don't and Edward Tufte's The Visual Display of Quantitative Information, with original ideas thrown in as well.

It makes me sad to think that people actually need to be told some of the information in this book, like “Check the y-axis on any chart presented by a politician”, or that snopes.com and Consumer Reports are good places to check the veracity of claims. However, it seems like people need to be told (again), so I'm glad that somebody's doing the telling. Still, will the happy time ever come where grown-ups don't need to be told this, like they don't need to be told not to stick their finger in an electrical outlet?

To be fair, there were moments when I needed to read things two or three times, moving my lips, and not (I flatter myself) because I am dumber than the average clam, but because my whiskey-addled brain shot predictably to the “intuitive” – but wrong – answer. Example: a con artist has three cards. One is red on both sides, one is white on both sides, the third is red on one side and white on the other. He shows you the card that is red on both sides. Then he shows you one side of a card – it is white. Is it an even-money bet that the other side is red? It seemed like it was to me, even though I knew this is a book largely about deceptive practices. So I was happy to be schooled on my (embarrassingly obvious in retrospect) mistake, which was not considering that the con artist could be showing me either of two sides of the white card, meaning the chance of the other side being red is one in three, not one in two.

Similarly, the author's, and Nate Silver's, best efforts notwithstanding, I'm having a hard time getting my mind around Bayesian analysis. As the author puts it (Kindle location 1117), Bayesian tools “… are so powerful, it's surprising they're not taught to us in high school.” I'm still super cheesed-off that we spent all that time learning trigonometry but I didn't find out about Bayesian analysis until my dotage.

My understanding was also obstructed by the lack, in my electronic galley copy, of graphic aid in the form of the 2x2 Bayesian squares to accompany the author's examples. (Instead, my copy just had clumps of numbers in gaps in the text. The intended graphic could be reconstructed with a pencil and paper, using clues from the number clumps and the narrative, if you move your lips slowly enough.) I think and hope the publisher will clean this up for the commercial release of the book.

Also, I hope someone will check the arithmetic on the Bayesian squares, for example, the one at location 1111, but also squares closer to the end of the book, because I think some of the figures are in error and don't add up – perhaps a typographic error.

BTW, what's the difference between an ebook and an “enhanced” ebook, besides the $2 price that is in evidence at the publisher's web page. Is an enhanced ebook like the “premium” version of smartphone apps, meaning, one where all the features actually work correctly, more or less?

Thanks to those nice people at Penguin Random House and Netgalley for a free electronic copy of this book.

[Jamie Smith · Rating 4 out of 5]

This book was not on my reading list, but I happened to see it while browsing my library’s ebook shelves and decided to take a chance on it. It was better than I anticipated, a good introduction to critical thinking skills. It starts with a section called Evaluating Numbers and moves from the very basics, such as statistical mean-median-mode to a discussion of chart shenanigans like hiding data and playing with multiple axes. It then abstracts the discussion from specifics to general observations of how data is collected and the questions we should ask about how it is analyzed, aggregated, and described. This leads to a theme that will be repeated throughout the book, that no one should accept assertions at face value. There are many, many ways to mislead, both accidentally and intentionally, and in the internet age entire websites and news organizations exist to manipulate and misrepresent information for political purposes.

One of the chapters in Section One is on probabilities, and has the clearest explanation of Bayes’ Theorem I have come across, complete with some excellent examples, including a horrific one where doctors who did not understand how to distinguish real positive and negative results from false positives and false negatives convinced hundreds of women to undergo major surgery for breast cancer which the vast majority of them never had.

The second section is Evaluating Words, and moves from statistics to psychology and sociology. It looks at what makes someone an expert, and makes a point we should all remember, that a person who is an expert in one area could be out of their depth when speaking about others. The fact that someone has a PhD in one field does not necessarily mean they know what they are talking about when they speak on another, and the author provides several examples to make his point. This section made me think about two such examples which are not in the book: when the NFL was finally forced to study head trauma among current and former players, they showed their contempt for the process by putting in charge not a neurologist or a brain scientist, but a dermatologist. And when the Trump administration wanted plausible-sounding medical advice from a doctor who would say what he was told to say about Covid, they found a pliant radiologist, not a qualified epidemiologist.

The book’s final section is Evaluating the World and is a general discussion of how science works and how to recognize logical fallacies. There are also some good examples of how statistics can get misused in court.

A Field Guide to Lies will make you think about how you think: the things you know, the things that you don’t, the things that you might know but don’t know that you know, and the ones you don’t even know that you don’t know. Among the most dangerous of these, and a kind which plagues modern life and policy discussions, are the things that people believe that aren’t true. As Mark Twain (perhaps) said, “It ain’t what you don’t know that gets you into trouble. It’s what you know for sure that just ain’t so.” Think about QAnon, whose followers fanatically believe in outlandish and ridiculous things and are immune to facts and logic – any attempts to prove them wrong are interpreted as more evidence that they are right. While they may be one particularly toxic and pathetic example, there are plenty of people who get their news from biased and partisan sources, and never consider how they are being manipulated. These include not just your crazy uncle who goes on and on about conspiracies and cabals, but members of Congress, who are setting policy for the country. We all need to do our part to ensure that we understand what we believe, and why, and how we have come to trust the sources that back up our beliefs. These are dangerous times.

[David · Rating 3 out of 5]

You could argue reading this is timely in the lead up to the 2016 elections but it speaks to a nuance that is completely lacking in this particular campaign.

It’s more about the skewing of stats, presenting information that favours your viewpoint, logical fallacies. And it ties it into Fox News polls, autism claims, 9/11 truthers, unknown unknowns and more.

And while the sly authorial voice does occasionally peek out it reads like a first year textbook. There’s the missed potential to have more fun with this but it instead, seriously and perhaps appropriately given the nature of the book, resorts to cold hard logical truths and talks of bimodal distributions and Bayesian probability.

Still, 3 out of 4 dentists agree that this is better than 50% of the books out there.

[Christy Hammer · Rating 5 out of 5]

Finished this just in time to order it for fall! I'll swap it for Asking the Right Questions: A Guide to Critical Thinking, a remarkable book for its small size and clear, non-jargon prose, but it's just not cutting it anymore in the Trump era. (I'll still use Huff's classic How to Lie with Statistics.)

[Atila Iamarino · Rating 4 out of 5]

Bom livro sobre leitura crítica para tempos modernos que passa por um pouco de tudo. Sei de bons exemplos mais a fundo de cada tópico, mas vale pela obra toda, especialmente porque economiza a leitura de vários livros. Boas descrições de como se mente como estatísticas com anedotas bem ilustrativas, algo que o The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day cobre mais profundamente. Uma noção do que é informação científica, como ela é coletada e como muda, algo que o The Half-life of Facts: Why Everything We Know Has an Expiration Date cobre em mais detalhes. Pontos sobre como fatos são postados online e o que se perde ou não, parte do que o Smarter Than You Think: How Technology is Changing Our Minds for the Better fala. E uma noção do peso que a informação científica publicada em diferentes meios (jornais, artigos, reviews e meta-análises), que é mais detalhada e bem explicada no Snake Oil Science: The Truth about Complementary and Alternative Medicine. Se você não conhece alguma(s) dessas áreas, pode ser uma boa introdução.

[Amirography · Rating 5 out of 5]

A wonderfully well written book, on how to recognize fallacies and biased perspectives and to immune ourselves from being stuck with false beliefs.

[Bobi · Rating 2 out of 5]

This book joins a growing list of 'skeptic' sites/books/authors and as such is deeply skewed to orthodox anti-conspiratorial explanations. Being an academic, the author is beholden to the system that puts bread on his table. He skips from topic to topic too quickly and doesn't delve into enough details to put conspiracy theories to bed - he simply dismisses them with some form of simplistic analysis. A good example would be his too-brief treatment of 911 is which he places great weight on so-called experts - experts that only seemed to cast doubt on whether the fuel available could raise the temperature of steel enough and then asks us to consider all the extra fuel pre-existing in the building (paper, carpets, etc). He forgot that oxygen was the limiting factor, not the fuel. Thus he dismisses the supposedly unlikely (but popular) explanation of controlled demolition. He rejects the unlikely possibility of it being undertaken by The government without considering that it could be ANOTHER governments or other organizations with sophisticated (enough) resources. Inexplicably he also completely ignores building 7!!! Maybe he'll get to it later in the book, if i can last that long. In the meantime, several towers have burned quite nicely without falling down!

His treatment of climate deniers and medicine is similarly skewed toward orthodoxy, with no probing of the the herd effect within his sacred ivory tower in supporting answers preferred by (political) funding agencies. Thus was Galileo found guilty, and while he does acknowledge such possibilities, he steers clear of deep analysis.

Being an expert of course, he can and does outline many genuine statistical problems and sleights of hand that we should indeed become more aware of and for this he deserves praise. But the gullible will fall for such expertise and fail to think critically about which side he might be on.

[Tyera · Rating 2 out of 5]

Far more about statistics and scientific studies than expected, and not really written for those of us who do understand the scientific method and statistics.
In addition, Levitin switches too quickly between examples to let each one have its proper weight, almost like he's flipping among news sources, assuming the reader is flipping along as well. Some in-text sourcing might help resolve this issue... now that I think about it, I think Levitin could benefit from a good newswriting class himself.

Meh, I lack the energy to detail the ways I think this could be better. For me, it was not a very valuable read. But it's concerning to think there may be a lot of people who don't know or trust these things. So perhaps it is a valuable book for a different audience.

[Práxedes Rivera · Rating 4 out of 5]

This is the perfect book for the fake news era: a step by step guide to identifying and avoiding the most common methods of deceit utilized in mass media. Levitin breaks it down into sections examining dubious statistics, deceitful uses of language, and case studies.

As a librarian, my job is to connect people with relevant and reliable information. This book gives readers a checklist of things to look for before believing (or worse, repeating) bad data. Most definitely a worthwhile read.

[Camelia Rose · Rating 5 out of 5]

A Field Guide to Lies: Critical Thinking in the Information Age is a thoroughly researched and easy to understand book on critical thinking. Highly recommended for readers 14+.

The book is divided into three parts:
Part One: Evaluating Numbers
Part Two: Evaluating Words
Part Three: Evaluating the World

Part One is the heaviest: how numbers and graphs can fool you; how statistics work; how data is collected/reported and why it matters; what probabilities really mean and how to calculate them. Each topic comes with real world examples. Part Two: why and how to decide whether to trust the secondhand knowledge obtained from elsewhere; how to recognize expertise (expertise tends to be narrow, so, a general physician may not know enough about epidemiology); basic rules in weighing different explanations of a question, etc...

In the first chapter of Part Three, How Science Works, the author explains what scientific reasoning means, the basics of logic (deduction, induction and abduction). Chapter 2 Logic Fallacy: why correlation is not equivalent to causation. Chapter 3 Knowing What You Don’t Know. Four real world use cases are described.

Don't be discouraged by the complexity of critical thinking. It is important and totally worth the effort. Remember: it is ok to change your mind when new evidence comes. It is also important to accept that there are many uncertainties in this world, and some things just can not be known for the time being.

PS: The book was published in 2016, just before the 2016 US presidential election. Imagine the amount of new materials available to the author, had he written this book today.

[Ilaria · Rating 5 out of 5]

Daniel Levitin's Field guide presents a guide for putting in practice critical thinking, ranging from analyzing how numbers are presented in graphs, to applying Bayesian probabilities to court cases and life's decision, to recognizing logical fallacies and much more. The style is simple and the tone is sometimes colloquial. From what I understood by looking at previous reviews, some people found this book eye-opening, others felt that we should already know how to go about misinformation and counterknowledge and it seems like they didn't get much value out of it. To me, even people who are "questioners" or work in science and research can find lots of value into this book, as I did (and pass it to others that might benefit from this read even more!).
How did the Field guide change me? It made me more inquisitive and also made me feel truly responsible for the outcome of the decisions I made according to the information I have handy.

[Erik · Rating 2 out of 5]

Ultimately falls into an awkward gap, being conceptionally fairly basic...very familiar to anyone who has taken logic and stats classes. On the other, my initial hope that it would be full of amusing uses of bad statistics and logic to at least entertain if not educating wasn't fully gratified either.

[Sarah · Rating 3 out of 5]

I’ve always heard that numbers don’t lie. Well, they do! Can we believe experts? Can we ever trust the media? Levitin shows how statistics on issues like crime rates or house prices are tweaked to distort and manipulate.
There are chapters on probabilities and on correlation vs causation. He even goes into illusionists like David Blaine and why we can’t always believe what we see. An enlightening and entertaining read that will make me a more critical thinker.

[Zain Hashmy · Rating 3 out of 5]

This is one of those rare books that I feel does not deserve a proper review. It sits squarely in the area of books that are not good enough to be praised, but not bad enough to be ridiculed either.
The title was what drew me to the book, because the sheer amount of content that I consume in an average day is higher than average, making the chances that I am exposed to false claims also higher than most people. To separate the wheat from the chaff, quickly and efficiently and to use fancy terms to beat the crap out of people who use bad logic(I'm referring to all those idiots who've forwarded a whatsapp message without checking the facts), I thought this book would be a handy supplement.
Unfortunately the book does not live up to it's claims. The fundamental problem with writing a book like this is that it's a fine line to walk. In this case, the author was not able to toe that line well enough. A book like this needs to either be entertaining enough for the average person to read, or enlightening enough for the average scientist or technical reader to relish. This book does neither of those things, since the writing style is mostly dry and the analyses are mundane. It's nothing that would impress a technical reader, and an average person would get bored and give up at the ten percent mark.
That being said, I did learn some new things from the book, and it's not a complete disaster, but it doesn't live up to the title of being a field guide to lies.
The same book if written by a more experienced author, might be a lot more engaging.

Summary: Don't read it.

[Renee Godding · Rating 3 out of 5]

3.5/5 stars

In this day and age, we are constantly bombarded with information: some of it correct, some of it partially correct, confusing or misleading, and some of it blatantly wrong.
This book is a good introduction into critical reading and judging the information presented to you. It’s not the most in-depth book, and I have to say that I didn’t really learn too much from it, yet it’s a wonderful concise summary of the most important things to consider.
Looking critically at the world around us is a skill I would wish for everybody and i think many people would benefit greatly from the stepping stone this book presents.

[Bernard O'Leary · Rating 4 out of 5]

You would think that most of the information in this book – verifying sources, avoiding fallacious logic, basic statistics and so on – would be such common knowledge as for this book to be totally superfluous. Like, surely people know all this stuff, right?



Fair point.

It's an articulate explainer of quite basic rationalism, although I have a feeling that the people who need to read it probably won't.

[Will Ansbacher · Rating 3 out of 5]

A compact and solidly-written guide for those who aren’t too familiar with statistics, probability and logic, but despite the catchy title that appears to promise a lot, Calling Bullshit was stylistically better and more engaging.

Although Levitin doesn’t talk down to his audience, he seems to have seriously underestimated the range of abilities in the group he’s writing for. So, someone who has difficulties with the concept of averages and offset graph axes is unlikely to be able to follow much of the discussion of conditional probabilities – useful though they are - that make up a great deal of this book.

Following the statistical section “(Evaluating numbers”), there is a good but quite short one on critical thinking and expertise in general (“Evaluating Words”), but then it’s back to the statistic-heavy “Evaluating the World” on how science operates, which amplifies much of what is in his first part.

Frankly, there are many more examples of conditional probabilities than are really necessary to get his points across. He wonders at one point why the topic isn’t taught in high school. I don’t know about that, but if it isn’t maybe that’s because it is too easy to confuse learners or readers?
Because he does just that in one of his examples – that of mistaking “the probability that a woman has cancer given that she is in a high-risk group”, for “the probability she is in a high-risk group given that she has cancer”. I don’t mean Levitin made that mistake, but in explaining the consequences of that common fallacy his working is inaccurate enough to have confused me for a while.

So in short, it turns out that the field guide isn’t that comprehensive as the “lies” are mainly restricted to those you’d encounter in the social sciences. Well, not too surprising I guess, Levitin is a professor of Social Sciences.

[Ana · Rating 3 out of 5]

While I wish the tone were less dry and textbooklike, the information is very, very useful.

[Ihor Kolesnyk · Rating 5 out of 5]

Для тих, кому цікаве критичне мислення і механізми раціоналізації = фільтрування знання від брехні.
У книзі дуже багато різни х прикладів, частина із яких знайома усім, але деякі потребують заглиблення у тему.

[Scott · Rating 4 out of 5]

Statistically, 1 out of every 1 me knows less about Bayesian analysis than I think I do.

[Dave · Rating 3 out of 5]

As a book, it's good: occasionally funny, excellent examples, scrupulously fair (the only mention of Trump is followed by a similar example from Clinton)--maybe overscrupulous--and a good translation of complex logical arguments into simple language, though the Bayesian discussions get a little dense toward the end.

As a skill set, it is absolutely essential, especially nowadays. When I went to library school, I was dumbfounded that people don't recognize when information is unreliably sourced, and gobsmacked that they will trust obviously biased sources over others. This hasn't changed at all. Sometimes Levitin can't conceal his disgust with certain "lying weasels" (e.g., the vaccines-cause-autism wackos), but I found myself carrying much more outrage than Levitin communicates. I think maybe he feared a lawsuit.

We all need to know to distrust glib statistics, fudged information, and outright lies. Ask your librarian. And read this book, and any others you can that help show what's real and what's not. I also highly recommend The Signal and the Noise by Nate Silver.

[Nancy Mills · Rating 4 out of 5]

Great guide for recognizing spin. Spotlights the various ways data can be presented and numbers manipulated to lead you to conclusions presenters want you to believe. I listened to the audiobook and I probably should have read the paper version, as I imagine there are graphs and other helpful illustrations.

[Adrian Hoad-Reddick · Rating 5 out of 5]

This insightful book ought to be a multi discipline high school course that all students should take. It unravels mathematical mistruths and weasel words, and includes heaps of web literacy, logic and other ways to encourage mindful discrimination of truths in the face of the infoglut deluge.

[Buck · Rating 3 out of 5]

Not really what I was expecting; this is essentially a logic textbook for those of us not attending school. The ones who really need to read this, the anti-science, conspiracy theory, alternate-facts folks, wont.

[Morgan Stoker Taylor · Rating 4 out of 5]

Important book for today. The topic is my husbands soapbox and it helps us non-scientists wrap our minds around what information can be trusted. Basically it made me not trust anything.