---
product_id: 311352187
title: "Calling Bullshit: The Art of Skepticism in a Data-Driven World"
price: "€ 41.47"
currency: EUR
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reviews_count: 8
url: https://www.desertcart.gr/products/311352187-calling-bullshit-the-art-of-skepticism-in-a-data-driven
store_origin: GR
region: Greece
---

# Calling Bullshit: The Art of Skepticism in a Data-Driven World

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## Description

desertcart.com: Calling Bullshit: The Art of Skepticism in a Data-Driven World: 9780525509202: Bergstrom, Carl T., West, Jevin D.: Books

Review: Pure. Freaking. Brilliance. - This book instantly became my soul sister. If these guys have a fan club…I’d like to nominate myself as President. I loved this book so much. I work as a plain language expert and have said the phrase “I’m gonna call bullshit on that,” more times than I can begin to count. So much so, that I actually stumbled upon this book by chance—while I was looking on the internet for some type of poster or picture to hang in my office— that expressed this exact sentiment. I downloaded the audio book and loved it so much I bought a hard copy of it for both myself and my boss. I think this book should be required reading for every high school student before they head out into the world. It’s hilariously funny and written in plain language so hard concepts are easy to understand. My job is to make sure people understand what they read and can use that information to make informed decisions. But I don’t deal with research or data every day. I found that as I was editing other people’s work, it was sometimes hard to explain WHY things didn’t make sense—I just knew they didn’t. Reading this book actually improved my own skillset and made me better able to articulate exactly why research or data didn’t seem to make sense. I’ve actually used it several times as a reference. After working on the front lines of a pandemic, I think EVERYONE should read this book…and would highly recommend it to anyone. I thought it was funny and brilliant. I felt like these guys wrote it just to validate the things I say at work 🤣. This is now on my list of favorite books of all time—which is not an easy list to make—so that says something.
Review: Spirited and helpful primer - The book reminds me a lot of the 1954 classic How to Lie with Statistics, which jokingly referred to itself as a “manual for swindlers.” Like that brief book, this one has a light touch, clever writing, and fun examples as it alerts us to what goes wrong if people are naïve or dishonest in how they collect, analyze, and present data. The book covers what one would expect in a guide of this type—confirmation bias, selection bias, meaningless, statistics, and common cause and other fallacies of correlation and causation. This is all standard stuff. The book gains usefulness for contemporary readers when it shows how the online world, modern graphics, Big Data, AI, and modern academic publishing are contributing to the problem of knowing what is true. The chapter on visual displays of data is particularly fun. (I have never felt comfortable reading a 3D chart or table and now I know why). Another topical chapter covers the growing concerns about replication and reproducibility. Are we publishing too many studies with false positives? Are we ignoring many that are true but do not reveal anything groundbreaking? Which ones can we trust? The authors, while defending scientific endeavor, offer some tips for spotting error and ridiculousness. The final chapter is important because it warns us to be humble and not be jerks when we point out BS. Perhaps this should have been the first chapter in case readers neglect to finish the book. I taught a critical thinking course for several decades at the university level and worried that the tools of critical thinking were too easily weaponized and might become a cudgel that a brute could yield to bully others or a means to show off. This chapter addresses that tendency. Given the book’s strong effort to tie statistical error and deception to current trends, I am disappointed it did not cover “multiplier effects.” Politicians and activists love to imagine those. “Every dollar spent on this project will pay back $2.63 in benefits.” Similarly, it barely touched on the dangers of extrapolation (“if this trend continues”) and only as a tool for debunking. Bubbles, crashes, riots, and calls for draconian policies can be triggered by thinking too far ahead of the data. The book also does not address another current fear— that researchers on college campuses avoid topics or suppress results if they might cause offense to gun-shy undergrads or the politically correct. One drawback of the book is its occasional descent from casualness to breeziness. For example, it rather flippantly lumps climate skeptics in with people who believe in the healing power of crystals or creationism. That is dismissive and unfair given that politicians are floating proposals to address climate change that will cost many trillions of dollars. Many climate skeptics accept the evidence that the earth’s temperature rose due to human action but are not convinced that it is catastrophic or that spending trillions can do much to stop or reverse it. The authors criticize Steven Hayward’s line graph for making warming seem trivial by having the y-axis run from -10 to 110 degrees, but I sensed that his chart was satirical. It pokes fun at graphs that mark temperature increases in 5ths of a degree. Hayward’s y-axis covers the full range of temperatures most humans are likely to experience and shows that the average temperature is not pushing us anywhere near those extremes. The book could use an index.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Best Sellers Rank | #76,878 in Books ( See Top 100 in Books ) #30 in Medical Applied Psychology #37 in Political Corruption & Misconduct #46 in Popular Applied Psychology |
| Customer Reviews | 4.6 4.6 out of 5 stars (1,384) |
| Dimensions  | 5.13 x 0.71 x 8 inches |
| Edition  | Reprint |
| ISBN-10  | 0525509208 |
| ISBN-13  | 978-0525509202 |
| Item Weight  | 2.31 pounds |
| Language  | English |
| Print length  | 336 pages |
| Publication date  | April 20, 2021 |
| Publisher  | Random House Trade Paperbacks |
| Reading age  | 1 year and up |

## Images

![Calling Bullshit: The Art of Skepticism in a Data-Driven World - Image 1](https://m.media-amazon.com/images/I/81SinuF9x2L.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Pure. Freaking. Brilliance.
*by J***F on September 3, 2022*

This book instantly became my soul sister. If these guys have a fan club…I’d like to nominate myself as President. I loved this book so much. I work as a plain language expert and have said the phrase “I’m gonna call bullshit on that,” more times than I can begin to count. So much so, that I actually stumbled upon this book by chance—while I was looking on the internet for some type of poster or picture to hang in my office— that expressed this exact sentiment. I downloaded the audio book and loved it so much I bought a hard copy of it for both myself and my boss. I think this book should be required reading for every high school student before they head out into the world. It’s hilariously funny and written in plain language so hard concepts are easy to understand. My job is to make sure people understand what they read and can use that information to make informed decisions. But I don’t deal with research or data every day. I found that as I was editing other people’s work, it was sometimes hard to explain WHY things didn’t make sense—I just knew they didn’t. Reading this book actually improved my own skillset and made me better able to articulate exactly why research or data didn’t seem to make sense. I’ve actually used it several times as a reference. After working on the front lines of a pandemic, I think EVERYONE should read this book…and would highly recommend it to anyone. I thought it was funny and brilliant. I felt like these guys wrote it just to validate the things I say at work 🤣. This is now on my list of favorite books of all time—which is not an easy list to make—so that says something.

### ⭐⭐⭐⭐⭐ Spirited and helpful primer
*by K***D on September 19, 2020*

The book reminds me a lot of the 1954 classic How to Lie with Statistics, which jokingly referred to itself as a “manual for swindlers.” Like that brief book, this one has a light touch, clever writing, and fun examples as it alerts us to what goes wrong if people are naïve or dishonest in how they collect, analyze, and present data. The book covers what one would expect in a guide of this type—confirmation bias, selection bias, meaningless, statistics, and common cause and other fallacies of correlation and causation. This is all standard stuff. The book gains usefulness for contemporary readers when it shows how the online world, modern graphics, Big Data, AI, and modern academic publishing are contributing to the problem of knowing what is true. The chapter on visual displays of data is particularly fun. (I have never felt comfortable reading a 3D chart or table and now I know why). Another topical chapter covers the growing concerns about replication and reproducibility. Are we publishing too many studies with false positives? Are we ignoring many that are true but do not reveal anything groundbreaking? Which ones can we trust? The authors, while defending scientific endeavor, offer some tips for spotting error and ridiculousness. The final chapter is important because it warns us to be humble and not be jerks when we point out BS. Perhaps this should have been the first chapter in case readers neglect to finish the book. I taught a critical thinking course for several decades at the university level and worried that the tools of critical thinking were too easily weaponized and might become a cudgel that a brute could yield to bully others or a means to show off. This chapter addresses that tendency. Given the book’s strong effort to tie statistical error and deception to current trends, I am disappointed it did not cover “multiplier effects.” Politicians and activists love to imagine those. “Every dollar spent on this project will pay back $2.63 in benefits.” Similarly, it barely touched on the dangers of extrapolation (“if this trend continues”) and only as a tool for debunking. Bubbles, crashes, riots, and calls for draconian policies can be triggered by thinking too far ahead of the data. The book also does not address another current fear— that researchers on college campuses avoid topics or suppress results if they might cause offense to gun-shy undergrads or the politically correct. One drawback of the book is its occasional descent from casualness to breeziness. For example, it rather flippantly lumps climate skeptics in with people who believe in the healing power of crystals or creationism. That is dismissive and unfair given that politicians are floating proposals to address climate change that will cost many trillions of dollars. Many climate skeptics accept the evidence that the earth’s temperature rose due to human action but are not convinced that it is catastrophic or that spending trillions can do much to stop or reverse it. The authors criticize Steven Hayward’s line graph for making warming seem trivial by having the y-axis run from -10 to 110 degrees, but I sensed that his chart was satirical. It pokes fun at graphs that mark temperature increases in 5ths of a degree. Hayward’s y-axis covers the full range of temperatures most humans are likely to experience and shows that the average temperature is not pushing us anywhere near those extremes. The book could use an index.

### ⭐⭐⭐⭐ Deception is All Around Us
*by B***Y on January 12, 2021*

Misinformation is all around us. Sometimes, misleading information is purely an accident but other times, it is intentional in nature. False information is often fully intended to deceive, and its perpetrators have absolutely no regard for the truth. Their motive is to persuade by any means necessary and they will stop at nothing to achieve their goals. This problem is growing worse and worse every day and it is the subject of this book. Lots of people and organizations have agendas and if normal, honest means fail to achieve the intended results, then spreading false info is often the next step. For some, deception is such a common tool for them that they resort to it immediately. This book discusses several common types of deception, from cause and effect to distorted data visualization and much more. I like this book’s premise and I agree that spotting falsehoods- and using critical thinking in general- are important topics that need to be more thoroughly addressed. As I read, however, I started to feel a little pessimistic. When you think about all of the false information, fake news, deliberate deception, etc that exists all around us, it seems like an insurmountable task to try to wipe it out or at least diminish it from society. I still hold on to hope, but it is going to take a lot of education and effort to improve our collective critical thinking abilities so they we don’t so easily fall for these deceptions and this book is a good tool for this purpose. I enjoyed this book overall, but there is a section that discusses p- values that could cause some readers confusion. If you have ever worked in statistics or conducted research, you likely know what p-values are about. For everyone else, this chapter is going to go over their heads. I can understand why it was included, but it is a little much and its technical nature could cause some readers to conclude that the book and its topic are a little too complex for the average individual to understand. Still, this is an especially useful book overall and one that could benefit many members of the public who read it and absorb what it has to say. The use of deception is everywhere and we all need to do what we can to better develop our own deception detection system and help move the world in a more rational direction. Even if it means taking small baby steps at a time, it is imperative that we reverse the trend toward misinformation for a better tomorrow. This book can help accomplish exactly that.

## Frequently Bought Together

- Calling Bullshit: The Art of Skepticism in a Data-Driven World
- How to Lie with Statistics
- Naked Statistics: Stripping the Dread from the Data

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