Statistics Is Easy Quotes

And in August it will be fifty-two years together.” “Wow,” Oliver says. “That’s amazing.” “I wouldn’t call it amazing,” the woman says, blinking. “It’s easy when you find the right person.

How easy it is for so many of us today to be undoubtedly full of information yet fully deprived of accurate information.

It’s easy to lie with statistics, but it’s hard to tell the truth without them.

I don’t believe in statistics. I believe in calculus.

It was easy to be great. Every entertainer has a night when everything is clicking. These nights are accidental and statistical: Like lucky cards in poker, you can count on them occurring over time. What was hard was to be good, consistently good, night after night, no matter what the abominable circumstances.

Much of what we think of as cultural differences turn out to be differences in income.

It is easy to lie with statistics; it is easier to lie without them.

It’s easy when you find the right person.

Ten rules of thumb are still a lot for anyone to remember, so perhaps I should try to make things simpler. I realize that these suggestions have a common thread—a golden rule, if you like. Be curious.

It is not easy to become an educated person.

The writing of solid, instructive stuff fortified by facts and figures is easy enough. There is no trouble in writing a scientific treatise on the folk-lore of Central China, or a statistical enquiry into the declining population of Prince Edward Island. But to write something out of one's own mind, worth reading for its own sake, is an arduous contrivance only to be achieved in fortunate moments, few and far in between. Personally, I would sooner have written Alice in Wonderland than the whole Encyclopedia Britannica.

Statistics show that the nature of English crime is reverting to its oldest habits. In a country where so many desire status and wealth, petty annoyances can spark disproportionately violent behaviour. We become frustrated because we feel powerless, invisible, unheard. We crave celebrity, but that’s not easy to come by, so we settle for notoriety. Envy and bitterness drive a new breed of lawbreakers, replacing the old motives of poverty and the need for escape. But how do you solve crimes which no longer have traditional motives?

So the problem is not the algorithms, or the big datasets. The problem is a lack of scrutiny, transparency, and debate.

Not asking what a statistic actually means is a failure of empathy, too.

The viewer of television, the listener to radio, the reader of magazines, is presented with a whole complex of elements—all the way from ingenious rhetoric to carefully selected data and statistics—to make it easy for him to “make up his own mind” with the minimum of difficulty and effort. But the packaging is often done so effectively that the viewer, listener, or reader does not make up his own mind at all. Instead, he inserts a packaged opinion into his mind, somewhat like inserting a cassette into a cassette player. He then pushes a button and “plays back” the opinion whenever it seems appropriate to do so. He has performed acceptably without having had to think.

Statistics are somewhat like old medical journals, or like revolvers in newly opened mining districts. Most men rarely use them, and find it troublesome to preserve them so as to have them easy of access; but when they do want them, they want them badly.

A hammer looks like a useful tool to a carpenter; the nail has a different impression altogether

It is easy to lie with statistics. It is hard to tell the truth without it.

Van Meegeren wasn’t an artistic genius, but he intuitively understood something about human nature. Sometimes, we want to be fooled.

Creative business seminar. Basically a quick, impromptu brainwashing course to educate your typical corporate warriors. They use a training manual instead of sacred scriptures, with promotion and a high salary as their equivalent of enlightenment and paradise. A new religion for a pragmatic age. No transcendent elements like in a religion, though, and everything is theorized and digitalized. Very transparent and easy to grasp. And quite a few people get positive encouragement from this. But the fact remains that it’s nothing more than an infusion of the hypnotic into a system of thought that suits their goal, a conglomeration of only those theories and statistics that line up with their ultimate objectives.

It is too easy to think that ‘science’ is what happens now, that modernity and scientific thought are inseparable. Yet as Laura Snyder so brilliantly shows in this riveting picture of the first heroic age, the nineteenth century saw the invention of the computer, of electrical impulses, the harnessing of the power of steam – the birth of railways, statistics and technology. In ‘The Philosophical Breakfast Club’ she draws an endearing – almost domestic – picture of four scientific titans, and shows how – through their very ‘clubbability’ – they created the scientific basis on which the modern world stands.

We live in an era of social science, and have become accustomed to understanding the social world in terms of “forces,” “pressures,” “processes,” and “developments.” It is easy to forget that those “forces” are statistical summaries of the deeds of millions of men and women who act on their beliefs in pursuit of their desires. The

We live in an era of social science, and have become accustomed to understanding the social world in terms of “forces,” “pressures,” “processes,” and “developments.” It is easy to forget that those “forces” are statistical summaries of the deeds of millions of men and women who act on their beliefs in pursuit of their desires. The habit of submerging the individual into abstractions can lead not only to bad science (it’s not as if the “social forces” obeyed Newton’s laws) but to dehumanization.

Einstein, twenty-six years old, only three years away from crude privation, still a patent examiner, published in the Annalen der Physik in 1905 five papers on entirely different subjects. Three of them were among the greatest in the history of physics. One, very simple, gave the quantum explanation of the photoelectric effect—it was this work for which, sixteen years later, he was awarded the Nobel prize. Another dealt with the phenomenon of Brownian motion, the apparently erratic movement of tiny particles suspended in a liquid: Einstein showed that these movements satisfied a clear statistical law. This was like a conjuring trick, easy when explained: before it, decent scientists could still doubt the concrete existence of atoms and molecules: this paper was as near to a direct proof of their concreteness as a theoretician could give. The third paper was the special theory of relativity, which quietly amalgamated space, time, and matter into one fundamental unity. This last paper contains no references and quotes to authority. All of them are written in a style unlike any other theoretical physicist's. They contain very little mathematics. There is a good deal of verbal commentary. The conclusions, the bizarre conclusions, emerge as though with the greatest of ease: the reasoning is unbreakable. It looks as though he had reached the conclusions by pure thought, unaided, without listening to the opinions of others. To a surprisingly large extent, that is precisely what he had done.

If the story you’re reading is about health, there’s one place you should be sure to look for a second opinion: the Cochrane Collaboration.

Kahneman, Nobel laureate and one of the fathers of behavioral economics, calls overconfidence “the most significant of the cognitive biases.

Yes, it’s easy to lie with statistics—but it’s even easier to lie without them.*

curious person, however, enjoys being surprised and hungers for the unexpected.

A more plausible explanation is that we are drawn to surprising news, and surprising news is more often bad than good.

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.

Once you do know what the question actually is, you’ll know what the answer means. • Deep Thought (a supercomputer in Douglas Adams’s Hitchhiker’s Guide to the Galaxy)

When a measure becomes a target, it ceases to be a good measure.”)

the diagram “is to affect thro’ the Eyes what we may fail to convey to the brains of the public through their word-proof eyes.

The good stories are everywhere. They are not made memorable by their rarity; they are made forgettable by their ubiquity.

trust is easy to throw away and hard to regain.

we should ask who is missing from the data we’re being shown, and whether our conclusions might differ if they were included.

we should keep an open mind, asking how we might be mistaken, and whether the facts have changed.

Neuroscientific studies suggest that the brain responds in much the same anxious way to facts that threaten our preconceptions as it does to wild animals that threaten our lives.

The experimental subjects found it much easier to argue against positions they disliked than in favor of those they supported. There was a special power in doubt. Doubt

A hammer looks like a useful tool to a carpenter; the nail has a different impression altogether.

I just wish that Statistics was as easy as arranging numbers in chronological order, finding the median, lower and upper quartiles, and placing them on a Box and whisker's chart

The algorithm seemed to be really good at distinguishing the two rather similar canines; it turned out that it was simply labeling any picture with snow as containing a wolf. An example with more serious implications was described by Janelle Shane in her book You Look Like a Thing and I Love You: an algorithm that was shown pictures of healthy skin and of skin cancer. The algorithm figured out the pattern: if there was a ruler in the photograph, it was cancer.7 If we don’t know why the algorithm is doing what it’s doing, we’re trusting our lives to a ruler detector.

the “curse of knowledge” is a constant obstacle to clear communication: once you know a subject fairly well, it is enormously difficult to put yourself in the position of someone who doesn’t know it.

The viewer of television, the listener to radio, the reader of magazines, is presented with a whole complex of elements—all the way from ingenious rhetoric to carefully selected data and statistics—to make it easy for him to “make up his own mind” with the minimum of difficulty and effort. But the packaging is often done so effectively that the viewer, listener, or reader does not make up his own mind at all. Instead, he inserts a packaged opinion into his mind, somewhat like inserting a cassette into a cassette player. He then pushes a button and “plays back” the opinion whenever it seems appropriate to do so. He has performed acceptably without having had to think.

For a company to be valuable it must grow and endure, but many entrepreneurs focus only on short-term growth. They have an excuse: growth is easy to measure, but durability isn’t. Those who succumb to measurement mania obsess about weekly active user statistics, monthly revenue targets, and quarterly earnings reports. However, you can hit those numbers and still overlook deeper, harder-to-measure problems that threaten the durability of your business.

Just then, Larry recalled a conversation he had with a friend in Ireland, about the situation in Nepal between the King and the Maoists. The friend was sided with the Maoists, which was more or less his political leanings in any case, and stated that at least they were trying to help the people. So Larry had remarked upon the rising death rate, and how the Maoists are just as brutal as the security forces, yet the friend simply shrugged and said you have to expect some collateral damage in a revolution. Oh how he hates that phrase, as that makes it sound like the people’s lives are meant to be expendable, something that a person’s life should never be. Of course, it is very easy to disregard people you have never met, and who are certainly not your friends or family members. After all, in the eyes of an outsider, who is in no danger whatsoever, the people caught up in the situation are nothing more than simply statistics.

The French satirist Molière once wrote, “A learned fool is more foolish than an ignorant one.” Benjamin Franklin commented, “So convenient a thing it is to be a reasonable creature, since it enables us to find or make a reason for everything one has a mind to do.

The word “see” is often used as a direct synonym for “understand”—“I see what you mean.” Yet sometimes we see but we don’t understand; worse, we see, then “understand” something that isn’t true at all. Done well, a picture of data is worth the proverbial thousand words.

Specifically, Kahan identified “scientific curiosity.” That’s different from scientific literacy. The two qualities are correlated, of course, but there are curious people who know rather little about science (yet), and highly trained people with little appetite to learn more.

Quantitative historians who use statistical tools to study big-picture historical trends, created a vast database of research on more than 36,000 slave ship voyages that took place over four hundred years. They found that there was a revolt on at least one in ten of these voyages. That was a much higher number than anyone expected. Revolts were never easy, but revolts on slave ships in the middle of the Atlantic Ocean were basically suicide missions. Nonetheless, many captives chose death over this exceptionally horrid new kind of slavery. This type of resistance was so expensive and time-consuming for the slavers, these historians estimate that it prevented at least a million more people from being captured and entering the slave trade. So why would a revolt happen on one ship and not another? The quantitative historians couldn't find a clear pattern, other than that captives tried to revolt whenever they would. But one thing did stand out: The more women onboard a slave ship, the more likely a revolt. Let me emphasize this point: the more women onboard a slave ship, the more likely a revolt would occur.

One of the problems I face in life is that whenever I tell people that the Gaussian bell curve is not ubiquitous in real life, only in the minds of statisticians, they require me to “prove it”—which is easy to do, as we will see in the next two chapters, yet nobody has managed to prove the opposite

These examples should be models for communication, precisely because they inspire curiosity. “How does money influence politics?” is not an especially engaging question, but “If I were running for president, how would I raise lots of money with few conditions and no scrutiny?” is much more intriguing.

I’ve laid down ten statistical commandments in this book. First, we should learn to stop and notice our emotional reaction to a claim, rather than accepting or rejecting it because of how it makes us feel. Second, we should look for ways to combine the “bird’s eye” statistical perspective with the “worm’s eye” view from personal experience. Third, we should look at the labels on the data we’re being given, and ask if we understand what’s really being described. Fourth, we should look for comparisons and context, putting any claim into perspective. Fifth, we should look behind the statistics at where they came from—and what other data might have vanished into obscurity. Sixth, we should ask who is missing from the data we’re being shown, and whether our conclusions might differ if they were included. Seventh, we should ask tough questions about algorithms and the big datasets that drive them, recognizing that without intelligent openness they cannot be trusted. Eighth, we should pay more attention to the bedrock of official statistics—and the sometimes heroic statisticians who protect it. Ninth, we should look under the surface of any beautiful graph or chart. And tenth, we should keep an open mind, asking how we might be mistaken, and whether the facts have changed.

It is easy to find from the statistics pertaining to crime rate in a country that crimes against women are lowest in Islamic countries where women are dressed modestly and covered in burka (veil) in public places. Appropriate dressing, particularly in public places and before strangers can to some extent prevent crimes against women.

Psychologists call this “motivated reasoning.” Motivated reasoning is thinking through a topic with the aim, conscious or unconscious, of reaching a particular kind of conclusion. In a football game, we see the fouls committed by the other team but overlook the sins of our own side. We are more likely to notice what we want to notice.11

A lobby group seeking to deny the statistical evidence will always be able to point to some aspect of the current science that is not settled, note that the matter is terribly complicated, and call for more research. And these claims will sound scientific, even rather wise. Yet they give a false and dangerous impression: that nobody really knows anything.

Before I repeat any statistical claim, I first try to take note of how it makes me feel. It’s not a foolproof method against tricking myself, but it’s a habit that does little harm and is sometimes a great deal of help. Our emotions are powerful. We can’t make them vanish, nor should we want to. But we can, and should, try to notice when they are clouding our judgment.

asking about sampling errors and margins of error, debating if the number is rising or falling, believing, doubting, analyzing, dissecting—without taking the time to understand the first and most obvious fact: What is being measured, or counted? What definition is being used? Yet while this pitfall is common, it doesn’t seem to have acquired a name. My suggestion is “premature enumeration.

He did not believe in luck at all, good or bad. Gamblers believed in luck, and he was not a gambler. Never had been, never would be. John Henry Holliday believed in mathematics, in statistics, in the computation of odds. Fifty-two cards in a deck. Make it easy. Say it's fifty. Any card has a 2 percent chance of being dealt from a full deck. Keep track of what's out. Adjust the probabilities as the hand progresses.

The importance of the base rate was made famous by the psychologist Daniel Kahneman, who coined the phrase “the outside view and the inside view.” The inside view means looking at the specific case in front of you: this couple. The outside view requires you to look at a more general “comparison class” of cases—here, the comparison class is all married couples. (The outside view needn’t be statistical, but it often will be.)

The English word Atonement comes from the ancient Hebrew word kaphar, which means to cover. When Adam and Eve partook of the fruit and discovered their nakedness in the Garden of Eden, God sent Jesus to make coats of skins to cover them. Coats of skins don’t grow on trees. They had to be made from an animal, which meant an animal had to be killed. Perhaps that was the very first animal sacrifice. Because of that sacrifice, Adam and Eve were covered physically. In the same way, through Jesus’ sacrifice we are also covered emotionally and spiritually. When Adam and Eve left the garden, the only things they could take to remind them of Eden were the coats of skins. The one physical thing we take with us out of the temple to remind us of that heavenly place is a similar covering. The garment reminds us of our covenants, protects us, and even promotes modesty. However, it is also a powerful and personal symbol of the Atonement—a continuous reminder both night and day that because of Jesus’ sacrifice, we are covered. (I am indebted to Guinevere Woolstenhulme, a religion teacher at BYU, for insights about kaphar.) Jesus covers us (see Alma 7) when we feel worthless and inadequate. Christ referred to himself as “Alpha and Omega” (3 Nephi 9:18). Alpha and omega are the first and last letters of the Greek alphabet. Christ is surely the beginning and the end. Those who study statistics learn that the letter alpha is used to represent the level of significance in a research study. Jesus is also the one who gives value and significance to everything. Robert L. Millet writes, “In a world that offers flimsy and fleeting remedies for mortal despair, Jesus comes to us in our moments of need with a ‘more excellent hope’ (Ether 12:32)” (Grace Works, 62). Jesus covers us when we feel lost and discouraged. Christ referred to Himself as the “light” (3 Nephi 18:16). He doesn’t always clear the path, but He does illuminate it. Along with being the light, He also lightens our loads. “For my yoke is easy,” He said, “and my burden is light” (Matthew 11:30). He doesn’t always take burdens away from us, but He strengthens us for the task of carrying them and promises they will be for our good. Jesus covers us when we feel abused and hurt. Joseph Smith taught that because Christ met the demands of justice, all injustices will be made right for the faithful in the eternal scheme of things (see Teachings, 296). Marie K. Hafen has said, “The gospel of Jesus Christ was not given us to prevent our pain. The gospel was given us to heal our pain” (“Eve Heard All These Things,” 27). Jesus covers us when we feel defenseless and abandoned. Christ referred to Himself as our “advocate” (D&C 29:5): one who believes in us and stands up to defend us. We read, “The Lord is my rock, and my fortress, and my deliverer; my God, my strength, in whom I will trust; my buckler” (Psalm 18:2). A buckler is a shield used to divert blows. Jesus doesn’t always protect us from unpleasant consequences of illness or the choices of others, since they are all part of what we are here on earth to experience. However, He does shield us from fear in those dark times and delivers us from having to face those difficulties alone. … We’ve already learned that the Hebrew word that is translated into English as Atonement means “to cover.” In Arabic or Aramaic, the verb meaning to atone is kafat, which means “to embrace.” Not only can we be covered, helped, and comforted by the Savior, but we can be “encircled about eternally in the arms of his love” (2 Nephi 1:15). We can be “clasped in the arms of Jesus” (Mormon 5:11). In our day the Savior has said, “Be faithful and diligent in keeping the commandments of God, and I will encircle thee in the arms of my love” (D&C 6:20). (Brad Wilcox, The Continuous Atonement, pp. 47-49, 60).

(…) it may be seriously questioned whether the advent of modern communications media has much enhanced our understanding of the world in which we live.(…) Perhaps we know more about the world than we used to, and insofar as knowledge is prerequisite to understanding, that is all to the good. But knowledge is not as much a prerequisite to understanding as is commonly supposed. We do not have to know everything about something in order to understand it; too many facts are often as much of an obstacle to understanding as too few. There is a sense in which we moderns are inundated with facts to the detriment of understanding. (…) One of the reasons for this situation is that the very media we have mentioned are so designed as to make thinking seem unnecessary (though this is only an appearance). The packaging of intellectual positions and views is one of the most active enterprises of some of the best minds of our day. The viewer of television, the listener to radio, the reader of magazines, is presented with a whole complex of elements—all the way from ingenious rhetoric to carefully selected data and statistics—to make it easy for him to “make up his own mind” with the minimum of difficulty and effort. But the packaging is often done so effectively that the viewer, listener, or reader does not make up his own mind at all. Instead, he inserts a packaged opinion into his mind, somewhat like inserting a cassette into a cassette player. He then pushes a button and “plays back” the opinion whenever it seems appropriate to do so. He has performer acceptably without having had to think.

...computer technology functions more as a new mode of transportation than as a new means of substantive communication. It moves information—lots of it, fast, and mostly in a calculating mode. The computer, in fact, makes possible the fulfillment of Descartes’ dream of the mathematization of the world. Computers make it easy to convert facts into statistics and to translate problems into equations. And whereas this can be useful (as when the process reveals a pattern that would otherwise go unnoticed), it is diversionary and dangerous when applied indiscriminately to human affairs.

More often than not, in fact, outstanding performance will become less outstanding. Conversely, very poor performance will improve. It is easy to imagine social, psychological, or even political reasons for this observation, but reasons are not required. The phenomenon is purely statistical. Extreme observations in one direction or the other will tend to become less extreme, simply because past performance is not perfectly correlated with future performance. This tendency is called regression to the mean (hence the technical term nonregressive for matching predictions, which fail to take it into account).

Downey’s documented evidence of the hatred and misunderstanding of atheists makes it easy to believe that it is, indeed, virtually impossible for an honest atheist to win a public election in America. There are 435 members of the House of Representatives and 100 members of the Senate. Assuming that the majority of these 535 individuals are an educated sample of the population, it is statistically all but inevitable that a substantial number of them must be atheists. They must have lied, or concealed their true feelings, in order to get elected. Who can blame them, given the electorate they had to convince?

One important error that the judges make is what American legal scholar Cass Sunstein calls “current offense bias”—that is, when they make decisions about bail, they focus too much on the specific offense the defendant has been accused of. Defendants whose track record suggests they’re a high risk are treated as low risk if they’re accused of a minor crime, and defendants whose track record suggests they’re low risk are treated as high risk if the current offense is serious. There’s valuable information here that the algorithm puts to good use, but the human judges—for all their intelligence, experience, and training—tend to overlook it.

the feeling that they are. Psychologists have a name for our tendency to confuse our own perspective with something more universal: it’s called “naive realism,” the sense that we are seeing reality as it truly is, without filters or errors.9 Naive realism can lead us badly astray when we confuse our personal perspective on the world with some universal truth. We are surprised when an election goes against us: Everyone in our social circle agreed with us, so why did the nation vote otherwise? Opinion polls don’t always get it right, but I can assure you they have a better track record of predicting elections than simply talking to your friends.

It’s a rather beautiful discovery: in a world where so many people seem to hold extreme views with strident certainty, you can deflate somebody’s overconfidence and moderate their politics simply by asking them to explain the details. Next time you’re in a politically heated argument, try asking your interlocutor not to justify herself, but simply to explain the policy in question. She wants to introduce a universal basic income, or a flat tax, or a points-based immigration system, or Medicare for all. OK, that’s interesting. So what exactly does she mean by that? She may learn something as she tries to explain. So may you. And you may both find that you understand a little less, and agree a little more, than you had assumed.

Draw a line down the middle of any room, and you will find group disparities in income, IQ, education, and age. Such disparities are not the result of societal discrimination. They are the result of statistical probability. But according to the Disintegrationists, disparities are automatically the result of discrimination, often relabeled under vague terms like “privilege,” “institutional racism,” or “patriarchalism.” The Disintegrationist philosophy therefore leads to this extraordinarily destructive logic: we must have equality of opportunity, which means unequal rights, because people are not inherently equal; any inequality in society is proof of inequality of opportunity. No system can survive under this logic: inequality of outcome is a feature inherent to humankind. But that’s precisely the point. The system must be destroyed.

We are living in a golden age of genetic research, with new technologies permitting the easy collection of genetic data from millions upon millions of people and the rapid development of new statistical methodologies for analyzing it. But it is not enough to just produce new genetic knowledge. As this research leaves the ivory tower and disseminates through the public, it is essential for scientists and the public to grapple with what this research means about human identity and equality. Far too often, however, this essential task of meaning-making is being abdicated to the most extreme and hate-filled voices. As Eric Turkheimer, Dick Nisbett, and I warned: If people with progressive political values, who reject claims of genetic determinism and pseudoscientific racialist speculation, abdicate their responsibility to engage with the science of human abilities and the genetics of human behavior, the field will come to be dominated by those who do not share those values.

There are several different frameworks one could use to get a handle on the indeterminate vs. determinate question. The math version is calculus vs. statistics. In a determinate world, calculus dominates. You can calculate specific things precisely and deterministically. When you send a rocket to the moon, you have to calculate precisely where it is at all times. It’s not like some iterative startup where you launch the rocket and figure things out step by step. Do you make it to the moon? To Jupiter? Do you just get lost in space? There were lots of companies in the ’90s that had launch parties but no landing parties. “But the indeterminate future is somehow one in which probability and statistics are the dominant modality for making sense of the world. Bell curves and random walks define what the future is going to look like. The standard pedagogical argument is that high schools should get rid of calculus and replace it with statistics, which is really important and actually useful. There has been a powerful shift toward the idea that statistical ways of thinking are going to drive the future.” —PETER THIEL

What we need,” I said, “are statistics on the amount of sugar cane standing in the field before the hurricanes came through Puerto Rico.” There was a stunned silence, as if they were afraid I had stumbled onto something that could turn out to be embarrassing for the Labor Department. “Well, it’s not that easy,” one of the Labor Department economists said. “We don’t have those statistics.” “I’ll bet the Department of Agriculture has them,” I said. “That’s still not the same as if we had them in the Department of Labor,” I was told. “Why can’t we get them from the Department of Agriculture?” I asked. “That’s easier said than done. First of all, we would have to make a request, going all the way up through channels to the Secretary of Labor. Then he would have to seek approval from the Secretary of Agriculture, who would then have to forward the request down the chain of command in the Department of Agriculture, to see if the data are available and can be released.” “Well,” I said, “John F. Kennedy says that a journey of a thousand miles must begin with a single step. Let me file the request.” That was 1960. I have yet to receive an official reply to my request.

What is it about the ancients,’ Pinker asks at one point, ‘that they couldn’t leave us an interesting corpse without resorting to foul play?’ There is an obvious response to this: doesn’t it rather depend on which corpse you consider interesting in the first place? Yes, a little over 5,000 years ago someone walking through the Alps left the world of the living with an arrow in his side; but there’s no particular reason to treat Ötzi as a poster child for humanity in its original condition, other than, perhaps, Ötzi suiting Pinker’s argument. But if all we’re doing is cherry-picking, we could just as easily have chosen the much earlier burial known to archaeologists as Romito 2 (after the Calabrian rock-shelter where it was found). Let’s take a moment to consider what it would mean if we did this. Romito 2 is the 10,000-year-old burial of a male with a rare genetic disorder (acromesomelic dysplasia): a severe type of dwarfism, which in life would have rendered him both anomalous in his community and unable to participate in the kind of high-altitude hunting that was necessary for their survival. Studies of his pathology show that, despite generally poor levels of health and nutrition, that same community of hunter-gatherers still took pains to support this individual through infancy and into early adulthood, granting him the same share of meat as everyone else, and ultimately according him a careful, sheltered burial.15 Neither is Romito 2 an isolated case. When archaeologists undertake balanced appraisals of hunter-gatherer burials from the Palaeolithic, they find high frequencies of health-related disabilities – but also surprisingly high levels of care until the time of death (and beyond, since some of these funerals were remarkably lavish).16 If we did want to reach a general conclusion about what form human societies originally took, based on statistical frequencies of health indicators from ancient burials, we would have to reach the exact opposite conclusion to Hobbes (and Pinker): in origin, it might be claimed, our species is a nurturing and care-giving species, and there was simply no need for life to be nasty, brutish or short. We’re not suggesting we actually do this. As we’ll see, there is reason to believe that during the Palaeolithic, only rather unusual individuals were buried at all. We just want to point out how easy it would be to play the same game in the other direction – easy, but frankly not too enlightening.

ON THE MODUS OPERANDI OF OUR CURRENT PRESIDENT, DONALD J. TRUMP "According to a new ABC/Washington Post poll, President Trump’s disapproval rating has hit a new high." The President's response to this news was "“I don’t do it for the polls. Honestly — people won’t necessarily agree with this — I do nothing for the polls,” the president told reporters on Wednesday. “I do it to do what’s right. I’m here for an extended period of time. I’m here for a period that’s a very important period of time. And we are straightening out this country.” - Both Quotes Taken From Aol News - August 31, 2018 In The United States, as in other Republics, the two main categories of Presidential motivation for their assigned tasks are #1: Self Interest in seeking to attain and to hold on to political power for their own sakes, regarding the welfare of This Republic to be of secondary importance. #2: Seeking to attain and to hold on to the power of that same office for the selfless sake of this Republic's welfare, irregardless of their personal interest, and in the best of cases going against their personal interests to do what is best for this Republic even if it means making profound and extreme personal sacrifices. Abraham Lincoln understood this last mentioned motivation and gave his life for it. The primary information any political scientist needs to ascertain regarding the diagnosis of a particular President's modus operandi is to first take an insightful and detailed look at the individual's past. The litmus test always being what would he or she be willing to sacrifice for the Nation. In the case of our current President, Donald John Trump, he abandoned a life of liberal luxury linked to self imposed limited responsibilities for an intensely grueling, veritably non stop two year nightmare of criss crossing this immense Country's varied terrain, both literally and socially when he could have easily maintained his life of liberal leisure. While my assertion that his personal choice was, in my view, sacrificially done for the sake of a great power in a state of rapid decline can be contradicted by saying it was motivated by selfish reasons, all evidence points to the contrary. For knowing the human condition, fraught with a plentitude of weaknesses, for a man in the end portion of his lifetime to sacrifice an easy life for a hard working incessant schedule of thankless tasks it is entirely doubtful that this choice was made devoid of a special and even exalted inspiration to do so. And while the right motivations are pivotal to a President's success, what is also obviously needed are generic and specific political, military and ministerial skills which must be naturally endowed by Our Creator upon the particular President elected for the purposes of advancing a Nation's general well being for one and all. If one looks at the latest National statistics since President Trump took office, (such as our rising GNP, the booming market, the dramatically shrinking unemployment rate, and the overall positive emotive strains in regards to our Nation's future, on both the left and the right) one can make definitive objective conclusions pertaining to the exceptionally noble character and efficiency of the current resident at 1600 Pennsylvania Avenue. And if one can drown out the constant communicative assaults on our current Commander In Chief, and especially if one can honestly assess the remarkable lack of substantial mistakes made by the current President, all of these factors point to a leader who is impressively strong, morally and in other imperative ways. And at the most propitious time. For the main reason that so many people in our Republic palpably despise our current President is that his political and especially his social agenda directly threatens their licentious way of life. - John Lars Zwerenz

While writing the article that reported these findings, Amos and I discovered that we enjoyed working together. Amos was always very funny, and in his presence I became funny as well, so we spent hours of solid work in continuous amusement. The pleasure we found in working together made us exceptionally patient; it is much easier to strive for perfection when you are never bored. Perhaps most important, we checked our critical weapons at the door. Both Amos and I were critical and argumentative, he even more than I, but during the years of our collaboration neither of us ever rejected out of hand anything the other said. Indeed, one of the great joys I found in the collaboration was that Amos frequently saw the point of my vague ideas much more clearly than I did. Amos was the more logical thinker, with an orientation to theory and an unfailing sense of direction. I was more intuitive and rooted in the psychology of perception, from which we borrowed many ideas. We were sufficiently similar to understand each other easily, and sufficiently different to surprise each other. We developed a routine in which we spent much of our working days together, often on long walks. For the next fourteen years our collaboration was the focus of our lives, and the work we did together during those years was the best either of us ever did. We quickly adopted a practice that we maintained for many years. Our research was a conversation, in which we invented questions and jointly examined our intuitive answers. Each question was a small experiment, and we carried out many experiments in a single day. We were not seriously looking for the correct answer to the statistical questions we posed. Our aim was to identify and analyze the intuitive answer, the first one that came to mind, the one we were tempted to make even when we knew it to be wrong. We believed—correctly, as it happened—that any intuition that the two of us shared would be shared by many other people as well, and that it would be easy to demonstrate its effects on judgments.

In contemporary Western society, buying a magazine on astrology - at a newsstand, say - is easy; it is much harder to find one on astronomy. Virtually every newspaper in America has a daily column on astrology; there are hardly any that have even a weekly column on astronomy. There are ten times more astrologers in the United States than astronomers. At parties, when I meet people that do not know I’m a scientist, I am sometimes asked “Are you a Gemini?” (chances of success, one in twelve), or “What sign are you?” Much more rarely am I asked “Have you heard that gold is made in supernova explosions?” or “When do you think Congress will approve a Mars Rover?” (...) And personal astrology is with us still: consider two different newspaper astrology columns published in the same city on the same day. For example, we can examine The New York Post and the New York Daily News on September 21, 1979. Suppose you are a Libra - that is, born between September 23 and October 22. According to the astrologer for the Post, ‘a compromise will help ease tension’; useful, perhaps, but somewhat vague. According to the Daily News’ astrologer, you must ‘demand more of yourself’, an admonition that is also vague but also different. These ‘predictions’ are not predictions; rather they are pieces of advice - they tell you what to do, not what will happen. Deliberately, they are phrased so generally that they could apply to anyone. And they display major mutual inconsistencies. Why are they published as unapologetically as sport statistics and stock market reports? Astrology can be tested by the lives of twins. There are many cases in which one twin is killed in childhood, in a riding accident, say, or is struck by lightning, while the other lives to a prosperous old age. Each was born in precisely the same place and within minutes of the other. Exactly the same planets were rising at their births. If astrology were valid, how could two such twins have such profoundly different fates? It also turns out that astrologers cannot even agree among themselves on what a given horoscope means. In careful tests, they are unable to predict the character and future of people they knew nothing about except their time and place of birth.

There is some feeling nowadays that reading is not as necessary as it once was. Radio and especially television have taken over many of the functions once served by print, just as photography has taken over functions once served by painting and other graphic arts. Admittedly, television serves some of these functions extremely well; the visual communication of news events, for example, has enormous impact. The ability of radio to give us information while we are engaged in doing other things—for instance, driving a car—is remarkable, and a great saving of time. But it may be seriously questioned whether the advent of modern communications media has much enhanced our understanding of the world in which we live. Perhaps we know more about the world than we used to, and insofar as knowledge is prerequisite to understanding, that is all to the good. But knowledge is not as much a prerequisite to understanding as is commonly supposed. We do not have to know everything about something in order to understand it; too many facts are often as much of an obstacle to understanding as too few. There is a sense in which we moderns are inundated with facts to the detriment of understanding. One of the reasons for this situation is that the very media we have mentioned are so designed as to make thinking seem unnecessary (though this is only an appearance). The packaging of intellectual positions and views is one of the most active enterprises of some of the best minds of our day. The viewer of television, the listener to radio, the reader of magazines, is presented with a whole complex of elements—all the way from ingenious rhetoric to carefully selected data and statistics—to make it easy for him to “make up his own mind” with the minimum of difficulty and effort. But the packaging is often done so effectively that the viewer, listener, or reader does not make up his own mind at all. Instead, he inserts a packaged opinion into his mind, somewhat like inserting a cassette into a cassette player. He then pushes a button and “plays back” the opinion whenever it seems appropriate to do so. He has performed acceptably without having had to think.

Business is business. It’s not always easy, but the outcome is fairly predictable. Relationships are messy. You have no data, no statistics. Nothing to justify taking the leap, except for emotion.

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The test statistics of a t-test can be positive or negative, although this depends merely on which group has the larger mean; the sign of the test statistic has no substantive interpretation. Critical values (see Chapter 10) of the t-test are shown in Appendix C as (Student’s) t-distribution.4 For this test, the degrees of freedom are defined as n – 1, where n is the total number of observations for both groups. The table is easy to use. As mentioned below, most tests are two-tailed tests, and analysts find critical values in the columns for the .05 (5 percent) and .01 (1 percent) levels of significance. For example, the critical value at the 1 percent level of significance for a test based on 25

The test statistics of a t-test can be positive or negative, although this depends merely on which group has the larger mean; the sign of the test statistic has no substantive interpretation. Critical values (see Chapter 10) of the t-test are shown in Appendix C as (Student’s) t-distribution.4 For this test, the degrees of freedom are defined as n – 1, where n is the total number of observations for both groups. The table is easy to use. As mentioned below, most tests are two-tailed tests, and analysts find critical values in the columns for the .05 (5 percent) and .01 (1 percent) levels of significance. For example, the critical value at the 1 percent level of significance for a test based on 25 observations (df = 25 – 1 = 24) is 2.797 (and 1.11 at the 5 percent level of significance). Though the table also shows critical values at other levels of significance, these are seldom if ever used. The table shows that the critical value decreases as the number of observations increases, making it easier to reject the null hypothesis. The t-distribution shows one- and two-tailed tests. Two-tailed t-tests should be used when analysts do not have prior knowledge about which group has a larger mean; one-tailed t-tests are used when analysts do have such prior knowledge. This choice is dictated by the research situation, not by any statistical criterion. In practice, two-tailed tests are used most often, unless compelling a priori knowledge exists or it is known that one group cannot have a larger mean than the other. Two-tailed testing is more conservative than one-tailed testing because the critical values of two-tailed tests are larger, thus requiring larger t-test test statistics in order to reject the null hypothesis.5 Many statistical software packages provide only two-tailed testing. The above null hypothesis (men and women do not have different mean incomes in the population) requires a two-tailed test because we do not know, a priori, which gender has the larger income.6 Finally, note that the t-test distribution approximates the normal distribution for large samples: the critical values of 1.96 (5 percent significance) and 2.58 (1 percent significance), for large degrees of freedom (∞), are identical to those of the normal distribution. Getting Started Find examples of t-tests in the research literature. T-Test Assumptions Like other tests, the t-test has test assumptions that must be met to ensure test validity. Statistical testing always begins by determining whether test assumptions are met before examining the main research hypotheses. Although t-test assumptions are a bit involved, the popularity of the t-test rests partly on the robustness of t-test conclusions in the face of modest violations. This section provides an in-depth treatment of t-test assumptions, methods for testing the assumptions, and ways to address assumption violations. Of course, t-test statistics are calculated by the computer; thus, we focus on interpreting concepts (rather than their calculation). Key Point The t-test is fairly robust against assumption violations. Four t-test test assumptions must be met to ensure test validity: One variable is continuous, and the other variable is dichotomous. The two distributions have equal variances. The observations are independent. The two distributions are normally distributed. The first assumption, that one variable is continuous and the other dichotomous,

While it is easy to lie with statistics, it is even easier to lie without them.

One of the lessons of the Hitler period is the stupidity of cleverness... Clever people have always made things easy for barbarians, because they are so stupid. It is the well-informed, farsighted judgements, the prognoses based on statistics and experience, the observations which begin: "I happen to be an expert in this field," it is the well-founded, conclusive statements which are untrue. Hitler was against intellect and humanity. But there is also an intellect which is against humanity: it is distinguished by well-informed superiority.

it is easy to lie with statistics, but easier to lie without them’.

The overwhelming importance of future profits is counterintuitive even in Silicon Valley. For a company to be valuable it must grow and endure, but many entrepreneurs focus only on short-term growth. They have an excuse: growth is easy to measure, but durability isn’t. Those who succumb to measurement mania obsess about weekly active user statistics, monthly revenue targets, and quarterly earnings reports. However, you can hit those numbers and still overlook deeper, harder-to-measure problems that threaten the durability of your business.

The United Nations, for example, has embraced a series of ambitious “Sustainable Development Goals” for 2030. But development experts are starting to call attention to a problem: we often don’t have the data we would need to figure out whether those goals have been met.

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.

The counterintuitive result is that presenting people with a detailed and balanced account of both sides of the argument may actually push people away from the center rather than pull them in. If we already have strong opinions, then we’ll seize upon welcome evidence, but we’ll find opposing data or arguments irritating. This biased assimilation of new evidence means that the more we know, the more partisan we’re able to be on a fraught issue.

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.

Van Meegeren admitted painting not only the work that had been found in Nazi hands, but Christ at Emmaus and several other supposed Vermeers.

Testing a hypothesis using the numbers that helped form the hypothesis in the first place is not OK.15

The Target algorithm hadn’t produced a superhuman leap of logic, but a very human one: it figured out exactly what you or I or anyone else would also have figured out, given the same information.

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.

A similar pattern holds if you measure scientific literacy: more scientifically literate Republicans and Democrats are further apart than those who know very little about science.17

Net wealth is a great way to measure riches, but not such a good way to measure poverty. Lots of people have zero, or less than zero. Some of them are destitute; others, like the junior doctor, are going to be fine.

But the psychologist Steven Pinker has argued that good news tends to unfold slowly, while bad news is often more sudden.

Nassim Taleb, author of The Black Swan, puts it succinctly: “To be completely cured of newspapers, spend a year reading the previous week’s newspapers.”27

There are some overtly racist and sexist people out there—look around—but in general what we count and what we fail to count is often the result of an unexamined choice, of subtle biases and hidden assumptions that we haven’t realized are leading us astray.

The shortest-lived creatures on the Disc were mayflies, which barely make it through twenty-four hours. Two of the oldest zigzagged aimlessly over the waters of a trout stream, discussing history with some younger members of the evening hatching. “You don’t get the kind of sun now that you used to get,” said one of them. “You’re right there. We had proper sun in the good old hours. It were all yellow. None of this red stuff.” “It were higher, too.” “It was. You’re right.

For obvious reasons, this particular flavor of survivorship bias is called “publication bias.” Interesting findings are published; non-findings, or failures to replicate previous findings, face a higher publication hurdle.