There are lots of book that claim to help you think. There is even a "smart thinking" category in some bookstores, presumably to distinguish the books it contains from the ones that promote dumb thinking. I have read many such books (and written a couple myself). This one is my favorite. It is packed with concrete examples and fun to read. You will genuinely be smarter after reading this book.
Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data.
“A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired
Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based…
I’m an economics professor, but I also have a column in Australia’s leading financial newspaper so I really appreciate authors who can tackle complex topics in an accessible manner. I’m also both extremely interested in and do academic research on topics to do with technologies like two-sided platforms, cryptocurrencies, blockchain, and artificial intelligence. All these books made me think harder about the big issues in these areas, and how to combine rigorous research with what is actually happening—often at breakneck speed—in the real-world digital economy.
This book helped me understand why advances in artificial intelligence are going to have a big impact on productivity and economic growth. I loved the analogies to old technologies like electrification of factories, and newer examples like how Team New Zealand used simulations to change racing tactics and boat design.
The book has an important, big idea at its heart. That idea is that AI helps organizations make better predications, and those better predictions allow organizations to be fundamentally redesigned to take advantage of this. This is where the AI productivity revolution comes from.
"What does AI mean for your business? Read this book to find out." -- Hal Varian, Chief Economist, Google Artificial intelligence does the seemingly impossible, magically bringing machines to life--driving cars, trading stocks, and teaching children. But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.
But in Prediction Machines, three eminent economists recast the rise of AI…
I’m a historian who’s spent far too much time thinking about how the color magenta contributed to climate change and why eighteenth-century humanitarians were obsessed with tobacco enemas. My favorite historical topics—like sensation, color, and truth—don’t initially seem historical, but that’s exactly why they need to be explored. I’ve learned that the things that seem like second nature are where our deepest cultural assumptions and unconscious biases hide. In addition to writing nonfiction, I’ve been lucky enough to grow up on a ranch, live in Paris, work as an interior design writer, teach high school and college, and help stray dogs get adopted.
I had never really given much thought to counting until I read this book, but in the very first chapter, Stone made me rethink everything I thought I knew about “one fish, two fish, red fish, blue fish.” She shows that every time we count, we’re making cultural assumptions. For example, what counts as a fish? And what makes the color of the fish more relevant than other features? Counting reveals that while these choices may seem intuitive, basic, and meaningless, they have very real impacts on people’s lives. Especially when we use numbers to measure things like merit, poverty, race, and productivity, those fundamental assumptions matter more than we care to admit.
Early in her extraordinary career, Deborah Stone wrote Policy Paradox, a landmark work on politics. Now, in Counting, she revolutionises how we approach numbers and shows how counting shapes the way we see the world. Most of us think of counting as a skill so basic that we see numbers as objective, indisputable facts. Not so, says Stone. In this playful-yet-probing work, Stone reveals the inescapable link between quantifying and classifying, and explains how counting determines almost every facet of our lives-from how we are evaluated at work to how our political opinions are polled to whether we get into…
I’m an avid fan of `More or Less,’ so this book was at the top of my list of must-reads, and I was not disappointed.
Common sense thinking seeps in by way of fascinating stories and interesting titbits. Fast-paced, light-hearted, and thought-provoking, Tim Harford does not disappoint with this book.
'Tim Harford is one of my favourite writers in the world. His storytelling is gripping but never overdone, his intellectual honesty is rare and inspiring, and his ability to make complex things simple - but not simplistic - is exceptional. How to Make the World Add Up is another one of his gems. If you're looking for an addictive pageturner that will make you smarter, this is your book' Rutger Bregman, author of Humankind
'Tim Harford could well be Britain's Malcolm Gladwell' Alex Bellos, author of Alex's Adventures in Numberland
I have always been fascinated by statistics (I’m a statistician by profession), and anything that tells a story of actual people and events has always captured my imagination. I have a particular affection for the quirky and offbeat, something that illustrates catastrophic failure, lack of common sense, a misplaced sense of entitlement and people who repeatedly tried but always fell short. I have a passion for black humour as it helps me to realise that, no matter how dark things look in my own life, there are others who have it much worse.
I was truly astonished to read a book that celebrates the dark side of life. It is full of unsavoury facts and includes many amazing lists. I found them really appalling, but at the same time was taken in by the sheer depravity of people from history.
In fact, I found myself reading this large volume twice as it was easy to forget just how nasty some of these characters were. I have recommended it to my friends, who also found it as fascinating as I did.
Prepare to be even more revolted, flabbergasted, appalled and entertained by this incredible follow-up collection of bizarre but absolutely true trivia. Nothing is too distasteful for this astonishing compendium, including scores of eclectic lists to amuse, astonish and appal your friends.
Entries include: 10 Road-kill Recipes History's 10 Most Murderous Regimes 10 Historic Sex Toys 10 People who Married Their Nieces 10 Deaths by Sex 10 People Killed by Falling Animals 10 Ancient Remedies Containing Body Parts 10 Flatalogical Facts 8 Most Violent National Anthems 15 Premature Obituaries 10 Unusual Royal Deaths 10 Cruel and Unusual Punishments 10 Notable Executions…
When I signed up for an introductory statistics course in college, I expected it would cover exactly what this book addresses. At that time, newspaper articles sometimes referred to the book that inspired this one, Darrell Huff’s How to Lie with Statistics.
I was excited to learn how to avoid getting snared by inadvertent and intentional flaws in public opinion polls, medical studies, and investment research. In a highly readable, entertaining style, Charles Wheelan arms his readers against all those pitfalls.
The somewhatabstruse quantitative methods actually taughtemphasized in the statistics course proved to be helpful professionally. But Wheelan’s statistical malpractice stories are both accessible to readers unfamiliar with the underlying math and informative to those who are.
Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.…
I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.
This provides a superb balance between technical aspects of R coding and the statistical methods that motivate its use. It's rare to find a book on topics like this that are written with Kabacoff's easygoing yet precise style, which makes it ideal for beginners. From my own experience, it is obvious the author has spent many years teaching this type of content, knowing where things deserve extra explanation up front and where other more technical details can be relegated to more advanced texts.
R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.
R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that…
I’ve wanted to be a philosopher since I read Plato’s Phaedo when I was 17, a new immigrant in Canada. Since then, I’ve been fascinated with time, space, and quantum mechanics and involved in the great debates about their mysteries. I saw probability coming into play more and more in curious roles both in the sciences and in practical life. These five books led me on an exciting journey into the history of probability, the meaning of risk, and the use of probability to assess the possibility of harm. I was gripped, entertained, illuminated, and often amazed at what I was discovering.
I am laughing out loud, even now that I am rereading this book for the umpteenth time. Fraudsters are so clever, and so is advertising. And then there is sloppy journalism with its “wow” statistics.
I like his book enormously, not least because of its witty illustrations. It is subversive, comic, and provocative, and it makes me wise to seductive, misleading practices–and it does so with a light touch.
From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff's lively and engaging primer clarifies the basic principles of statistics and explains how they're used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.
This book is fantastic. It shares exciting data stories from history (like how W. E. B. Du Bois used data and statistical reasoning to take down racist insurance practices during the US’s tragic Jim Crow era) and also covers modern applications like data in AI algorithms.
This book makes a great complement to Friendly and Wainer’s 2021 book: A History of Data Visualization and Graphic Communication.
From facial recognition-capable of checking us onto flights or identifying undocumented residents-to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the birth of eugenics in Victorian Britain to the development of Google search.
Expanding on the popular course they created at Columbia University, Chris Wiggins and Matthew Jones illuminate the ways in which data has long been used as a tool and a weapon in arguing…
I’m an Associate Professor in the University of Alabama’s Department of Philosophy. I worked as an FBI Special Agent before making the natural transition to academic philosophy. Being a professor was always a close second to Quantico, but that scene in Point Break in which Keanu Reeves and Patrick Swayze fight Anthony Kiedis on the beach made it seem like the FBI would be more fun than academia. In my current position as a professor at the University of Alabama, I teach in my department’s Jurisprudence Specialization. My primary research interests are at the intersection of philosophy of law, political philosophy, and criminal justice. I’ve written three books on policing.
I love this book because it reminds us of the many ways that technology can affect justice.
It is tempting to think sophisticated tactics such as “predictive policing” can solve all problems relating to human bias. However, Brayne shows that data and algorithms do not eliminate bias and discretion. Instead, high-tech police tools simply make bias less overt and visible, which erodes the public’s ability to hold the police accountable.
I especially enjoyed how the book flips the script, considering diverse ways to use these tools to help the public. For example, how can municipalities use technology to analyze the underlying factors that contribute to policing problems in the first place?
The scope of criminal justice surveillance, from the police to the prisons, has expanded rapidly in recent decades. At the same time, the use of big data has spread across a range of fields, including finance, politics, health, and marketing. While law enforcement's use of big data is hotly contested, very little is known about how the police actually use it in daily operations and with what consequences.
In Predict and Surveil, Sarah Brayne offers an unprecedented, inside look at how police use big data and new surveillance technologies, leveraging on-the-ground fieldwork with one of the most technologically advanced law…
