How to Make the World Add Up Quotes

“Four hundred thirty-six million people, with more than $100,000 but less than a million, collectively own another $125 trillion. Nearly 10 percent of the world’s adult population are in this second group. Those two groups, collectively, have most of the cash.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“wonderfully clarifying. Looking at the Global Wealth Report from Credit Suisse, the source of Oxfam’s claims, we can play with some of those numbers to shed more light on the topic.[*] Forty-two million people have more than a million dollars each, collectively owning about $142 trillion. A few of them are billionaires, but most are not. If you have a nice house with no mortgage in a place such as London, New York, or Tokyo, that might easily be enough to put you in this group. So would the right to a good private pension.[*] [19] Nearly 1 percent of the world’s adult population are in this group.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Az adatgyűjtés mellőzésének képessége a kormányok egyik legfontosabb és legkevésbé megértett hatalmi eszköze... A tudás felhalmozásának megtagadásával a döntéshozók hatalmat gyakorolnak mindannyiunk felett."
(Anna Powell-Smith)”
― Tim Harford, How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers

“A világ minden statisztikai szakértelme sem képes megakadályozni minket abban, hogy elhiggyük, amit nem kellene, és elvessük, amit nem kellene elvetnünk. A szakértelem mellé ugyanis szükség van arra is, hogy irányítani tudjuk a statisztikai állítások nyomán jelentkező érzelmi reakcióinkat.”
― Tim Harford, How to Make the World Add Up: Ten Rules for Thinking Differently About Numbers

“It is possible to take a stand not as a member of a political tribe but as someone who is willing to reflect and reason in a fair-minded manner.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“I worry about a world in which many people will believe anything, but I worry far more about one in which people believe nothing beyond their own preconceptions”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Yet sometimes the problem is not that we are too eager to believe something, but that we find reasons not to believe anything.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Scientists sometimes call this practice "HARKing"—HARK is an acronym for Hypothesizing After Results Known.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Psychologists are increasingly acknowledging the problem of experiments that study only "WEIRD" subjects–that is, Western, Educated, and from Industrialized Rich Democracies”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“van Meegeren like to accessorize his mansions with prostitutes, jewels, and prostitutes draped with jewels”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“In 2013, on the auspicious date of April 1, I received an email from Tetlock inviting me to join what he described as “a major new research program funded in part by Intelligence Advanced Research Projects Activity, an agency within the U.S. intelligence community.” The core of the program, which had been running since 2011, was a collection of quantifiable forecasts much like Tetlock’s long-running study. The forecasts would be of economic and geopolitical events, “real and pressing matters of the sort that concern the intelligence community—whether Greece will default, whether there will be a military strike on Iran, etc.” These forecasts took the form of a tournament with thousands of contestants; the tournament ran for four annual seasons. “You would simply log on to a website,” Tetlock’s email continued, “give your best judgment about matters you may be following anyway, and update that judgment if and when you feel it should be. When time passes and forecasts are judged, you could compare your results with those of others.” I did not participate. I told myself I was too busy; perhaps I was too much of a coward as well. But the truth is that I did not participate because, largely thanks to Tetlock’s work, I had concluded that the forecasting task was impossible. Still, more than 20,000 people embraced the idea. Some could reasonably be described as having some professional standing, with experience in intelligence analysis, think tanks, or academia. Others were pure amateurs. Tetlock and two other psychologists, Barbara Mellers (Mellers and Tetlock are married) and Don Moore, ran experiments with the cooperation of this army of volunteers. Some were given training in some basic statistical techniques (more on this in a moment); some were assembled into teams; some were given information about other forecasts; and others operated in isolation. The entire exercise was given the name Good Judgment Project, and the aim was to find better ways to see into the future. This vast project has produced a number of insights, but the most striking is that there was a select group of people whose forecasts, while they were by no means perfect, were vastly better than the dart-throwing-chimp standard reached by the typical prognosticator. What is more, they got better over time rather than fading away as their luck changed. Tetlock, with an uncharacteristic touch of hyperbole, called this group “superforecasters.” The cynics were too hasty: it is possible to see into the future after all. What makes a superforecaster? Not subject-matter expertise: professors were no better than well-informed amateurs. Nor was it a matter of intelligence; otherwise Irving Fisher would have been just fine. But there were a few common traits among the better forecasters.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“It’s clear why politicians in power might find it convenient to get advance notice of statistics so they can plan to crow about them if they’re good—or if they’re bad, to get their story straight or create a distraction. But it’s far from clear that this is in the public interest. Why shouldn’t everyone, on all sides of the debate, get access to the numbers at the same time, once they’re ready? (There is a compromise position: ministers could receive the statistics thirty minutes in advance and sit alone, without access to a cell phone, to compose a response. Quite apart from being pleasingly like sending powerful people back to sit exams, this is how journalists are sometimes given sensitive official releases. We cope. I was told a story about a Canadian statistician explaining this approach at an international gathering of colleagues. Her Russian counterpart chimed in with a question: “How does that approach work if the minister wishes to change the statistics?” Exactly.)”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“The success of Google Flu Trends became emblematic of the hot new trend in business, technology, and science: big data and algorithms. “Big data” can mean many things, but let’s focus on the found data we discussed in the previous chapter, the digital exhaust of web searches, credit card payments, and mobile phones pinging the nearest cell tower, perhaps buttressed by the administrative data generated as organizations organize themselves.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Another example: In 2012 Boston launched a smartphone app, Street Bump, which used an iPhone’s accelerometer to detect potholes. The idea was that citizens of Boston would download the app and, as they drove around the city, their phones would automatically notify city hall when the road surface needed repair—city workers would no longer have to patrol the streets looking for potholes. It’s a pleasingly elegant idea, and it did successfully find some holes in the road. Yet what Street Bump really produced, left to its own devices, was a map of potholes that systematically favored young, affluent areas where more people owned iPhones and had heard about the app. Street Bump offers us N = All in the sense that every bump from every enabled phone can be recorded. That is not the same thing as recording every pothole. The project has since been shelved.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Census taking is among the oldest ways of collecting statistics. Much newer, but with similar aspirations to reach everyone, is “big data.” Professor Viktor Mayer-Schönberger of Oxford’s Internet Institute, and coauthor of the book Big Data, told me that his favored definition of a big dataset is one where “N = All”—where we no longer have to sample, because we have the entire background population.[18”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“It could not. Sometimes you have to be there to understand—especially when a situation is fast-moving or contains soft, hard-to-quantify details, as is typically the case on the battlefield. The Nobel laureate economist Friedrich Hayek had a phrase for the kind of awareness that is hard to capture in metrics and maps: the “knowledge of the particular circumstances of time and place.” Social scientists have long understood that statistical metrics are at their most pernicious when they are being used to control the world, rather than try to understand it. Economists tend to cite their colleague Charles Goodhart, who wrote in 1975: “Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes.”[12] (Or, more pithily: “When a measure becomes a target, it ceases to be a good measure.”) Psychologists turn to Donald T. Campbell, who around the same time explained: “The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”[13]”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Trump is a man who polarizes opinion: you suspect that if he said ice cream was a pleasant treat on a sunny day, it would lead some Americans to refuse to eat anything but ice cream while others protested loudly outside ice cream parlors. So it was with COVID. The perverse and reckless refusal ever to wear a mask became a badge of pride for many of Trump’s supporters, while his opponents went to the opposite extreme—I noted one prominent tweet by a liberal American journalist explaining that the UK pandemic was “out of control” because people were not wearing masks as they walked in the park. To British eyes, the tweet just seemed bewildering: the evidence suggests that, mask or no mask, the risk of transmitting the virus while out for a stroll is very low. At the time of the tweet, late in January 2021, UK case numbers weren’t out of control either; they were rapidly falling. The tweet could be understood only as a salvo in a politically polarized battle about responsible mask use in which neither tribe was interested in figuring out the truth. Paradoxically, it can be much easier to spot tribalism at a distance. If you belong to the tribe of Republicans or Democrats, you’re too involved in the battle to think clearly. It is easier when—like your bemused British author—you belong to the tribe of puzzled outsiders.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Yet the logic of academic grants and promotions tells you to publish at once, and for goodness’ sake don’t prod it too hard.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Presumably this is because we personally experience our own localities, but we rely on the news for information about the wider world.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“But we can and should remember to ask who or what might be missing from the data we’re being told about.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Emaciated data-thin designs,” he warns, “provoke suspicions—and rightfully so—about the quality of measurement and analysis.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“In October 1949, less than two years after the trial began, Doll stopped smoking. He was thirty-seven, and had been a smoker his entire adult life. He and Hill had discovered that heavy smoking of cigarettes didn’t just double the risk of lung cancer, or triple the risk, or even quadruple the risk. It made you sixteen times more likely to get lung cancer.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Unfortunately, the selection mechanism is often some combination of beauty and shock value, rather than pertinence and accuracy.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“As time goes on, I get more and more convinced that the right method in investment is to put fairly large sums into enterprises which one thinks one knows something about and in the management of which one thoroughly believes.” Forget what the economy is doing; just find well-managed companies, buy some shares, and don’t try to be too clever. And if that approach sounds familiar, it’s most famously associated with Warren Buffett, the world’s richest investor—and a man who loves to quote John Maynard Keynes.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Adolf Hitler despised smoking. The Führer was no doubt pleased when German doctors discovered that cigarettes caused cancer. For obvious reasons, though, “hated by Nazis” was no impediment to the popularity of tobacco.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Scientific evidence is scientific evidence. Our beliefs around climate change shouldn’t skew left and right. But they do.16”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“He moved instead to an investment strategy that required no great macroeconomic insight. Instead, he explained, “As time goes on, I get more and more convinced that the right method in investment is to put fairly large sums into enterprises which one thinks one knows something about and in the management of which one thoroughly believes.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“For superforecasters, beliefs are hypotheses to be tested, not treasures to be guarded,” wrote Philip Tetlock after the study had been completed. “It would be facile to reduce superforecasting to a bumper-sticker slogan, but if I had to, that would be it.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“The likes of Google and Target are no more keen to share their datasets and algorithms than Newton was to share his alchemical experiments. Sometimes”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics

“Hearing the anecdote, it’s easy to assume that Target’s algorithms are infallible—that everybody receiving coupons for onesies and wet wipes is pregnant. But nobody ever claimed that it was true.”
― Tim Harford, The Data Detective: Ten Easy Rules to Make Sense of Statistics