Statistics Related Quotes

What we call ‘normal’ is a product of repression, denial, splitting, projection, introjection and other forms of destructive action on experience. It is radically estranged from the structure of being. The more one sees this, the more senseless it is to continue with generalized descriptions of supposedly specifically schizoid, schizophrenic, hysterical ‘mechanisms.’ There are forms of alienation that are relatively strange to statistically ‘normal’ forms of alienation. The ‘normally’ alienated person, by reason of the fact that he acts more or less like everyone else, is taken to be sane. Other forms of alienation that are out of step with the prevailing state of alienation are those that are labeled by the ‘formal’ majority as bad or mad.

There are thousands of things that can kill us—slightly more than eight thousand, according to the International Statistical Classification of Diseases and Related Health Problems compiled by the World Health Organization—and we escape every one of them but one. For most of us, that’s not a bad deal.

Todd, trust math. As in Matics, Math E. First-order predicate logic. Never fail you. Quantities and their relation. Rates of change. The vital statistics of God or equivalent. When all else fails. When the boulder's slid all the way back to the bottom. When the headless are blaming. When you do not know your way about. You can fall back and regroup around math. Whose truth is deductive truth. Independent of sense or emotionality. The syllogism. The identity. Modus Tollens. Transitivity. Heaven's theme song. The night light on life's dark wall, late at night. Heaven's recipe book. The hydrogen spiral. The methane, ammonia, H2O. Nucleic acids. A and G, T and C. The creeping inevibatility. Caius is mortal. Math is not mortal. What it is is: listen: it's true.

Statistically there’s only one crocodile-related human fatality per year in the whole of Australia.

Despite the earnest belief of most of his fans, Einstein did not win his Nobel Prize for the theory of relativity, special or general. He won for explaining a strange effect in quantum mechanics, the photoelectric effect. His solution provided the first real evidence that quantum mechanics wasn’t a crude stopgap for justifying anomalous experiments, but actually corresponds to reality. And the fact that Einstein came up with it is ironic for two reasons. One, as he got older and crustier, Einstein came to distrust quantum mechanics. Its statistical and deeply probabilistic nature sounded too much like gambling to him, and it prompted him to object that “God does not play dice with the universe.” He was wrong, and it’s too bad that most people have never heard the rejoinder by Niels Bohr: “Einstein! Stop telling God what to do.

Ah, marriage. The kind of union we have affects our children infinitely more than the schools we put them in, the activities we sign them up for, or the church we take them to. Our kids are learning relational habits by osmosis, and statistics say they’ll likely imitate what they witness at home.

What a well-designed forecasting system can do is sort out which statistics are relatively more susceptible to luck; batting average, for instance, is more erratic than home runs.

I conjecture, that human intuition is organized around casual, not statistical, relations.

At the quantum level our universe can be seen as an indeterminate place, predictable in a statistical way only when you employ large enough numbers. Between that universe and a relatively predictable one where the passage of a single planet can be timed to a picosecond, other forces come into play. For the in-between universe where we find our daily lives, that which you believe is a dominant force. Your beliefs order the unfolding of daily events. If enough of us believe, a new thing can be made to exist. Belief structure creates a filter through which chaos is sifted into order.

What comes full of virtue from the statistician’s desk may find itself twisted, exaggerated, oversimplified, and distorted-through-selection by salesman, public-relations expert, journalist, or advertising copywriter.

All life on our planet is related, and the readout of letters in DNA shows exactly how. By comparing DNA sequences, we can compute statistically how closely related we are to anything, from monkeys to marsupials, to reptiles, amphibians, fish, insects, crustaceans, worms, plants, protozoa, bacteria–you name it.

It is not the absolute degree of probability that matters, only its relative probability compared with other possible alternatives. It is the simple suggestion that the only valid reason for rejecting a statistical hypothesis is that some alternative explains the observed events with a greater degree of probability.

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.

away from or classed differently from a main or related body 2: a statistical observation that is markedly different in value from the others of the sample 1.

out·li·er \-,l()r\ noun 1: something that is situated away from or classed differently from a main or related body 2: a statistical

You no longer watch TV, it is TV that watches you (live),” or again: “You are no longer listening to Don’t Panic, it is Don’t Panic that is listening to you”—a switch from the panoptic mechanism of surveillance (Discipline and Punish [Surveiller et punir]) to a system of deterrence, in which the distinction between the passive and the active is abolished. There is no longer any imperative of submission to the model, or to the gaze “YOU are the model!” “YOU are the majority!” Such is the watershed of a hyperreal sociality, in which the real is confused with the model, as in the statistical operation, or with the medium. …Such is the last stage of the social relation, ours, which is no longer one of persuasion (the classical age of propaganda, of ideology, of publicity, etc.) but one of deterrence: “YOU are information, you are the social, you are the event, you are involved, you have the word, etc.” An about-face through which it becomes impossible to locate one instance of the model, of power, of the gaze, of the medium itself, because you are always already on the other side.

White folk commit the bulk of the crimes in our nation. And, beloved, it might surprise you that white folk commit the most violent crimes too. According to FBI statistics, black folk committed 36 percent of violent crime in 2015, while white folk committed 42 percent of violent crimes in the same year. White folk consistently lead all other groups in aggravated assault, larceny, illegal weapons possession, arson, and vandalism. And white folk are far more likely to target the vulnerable too. White folk lead the way in forcible rape. You’re also more likely to kill children, the elderly, significant others, family members, and even yourselves. White folk commit a majority of gang-related murders too. A majority of the homicide victims in this country are white. White folk are six times as likely to be murdered by a white person as they are to be taken out by a black “thug.” The white-on-white mayhem is profound, yet no one speaks of it in racial terms. That’s

out·li·er \-,l()r\ noun 1: something that is situated away from or classed differently from a main or related body 2: a statistical observation that is markedly different in value from the others of the sample

This book is an essay in what is derogatorily called "literary economics," as opposed to mathematical economics, econometrics, or (embracing them both) the "new economic history." A man does what he can, and in the more elegant - one is tempted to say "fancier" - techniques I am, as one who received his formation in the 1930s, untutored. A colleague has offered to provide a mathematical model to decorate the work. It might be useful to some readers, but not to me. Catastrophe mathematics, dealing with such events as falling off a height, is a new branch of the discipline, I am told, which has yet to demonstrate its rigor or usefulness. I had better wait. Econometricians among my friends tell me that rare events such as panics cannot be dealt with by the normal techniques of regression, but have to be introduced exogenously as "dummy variables." The real choice open to me was whether to follow relatively simple statistical procedures, with an abundance of charts and tables, or not. In the event, I decided against it. For those who yearn for numbers, standard series on bank reserves, foreign trade, commodity prices, money supply, security prices, rate of interest, and the like are fairly readily available in the historical statistics.

There are thousands of things that can kill us—slightly more than eight thousand, according to the International Statistical Classification of Diseases and Related Health Problems compiled by the World Health Organization—and we escape every one of them but one.

The Christian writer will feel that in the greatest depth of vision, moral judgment will be implicit, and that when we are invited to represent the country according to survey, what we are asked to do is to separate mystery from manners and judgment from vision, in order to produce something a little more palatable to the modern temper. We are asked to form our consciences in the light of statistics, which is to establish the relative as absolute. For many this may be a convenience, since we don't live in an age of settled belief; but it cannot be a convenience, it cannot even be possible, for the writer who is a Catholic. He will feel that any long-continued service to it will produce a soggy, formless, and sentimental literature, one that will provide a sense of spiritual purpose for those who connect the spirit with romanticism and a sense of joy for those who confuse that virtue with satisfaction. The storyteller is concerned with what is; but if what is is what can be determined by survey, then the disciples of Dr. Kinsey and Dr. Gallup are sufficient for the day thereof.

Statistics should consist not only in filling the register the size of a double bed sheet with useless numbers but in reducing these numbers to a quarter of a page and in relating them to one another, making it possible to see what happened and to anticipate what is going to happen.

a meta-study of developing and developed world nations found that the presence of a maternal grandmother was more beneficial for the survival and health of children than any other relative except a mother – that, statistically, kids are better off with a grandma around than a father.

Those who hold to the Christian faith see law as an ultimate order of the universe. It is the invariable factor in a variable world, the unchanging order in a changing universe. Law for the Christian is thus absolute, final, and an aspect of God's creation and a manifestation of His nature. In terms of this, the Christian can hold that right is right, and wrong is wrong, that good and evil are unchanging moral categories rather than relative terms. From an evolutionary perspective, however, we have a very different concept of law. The universe is evolving, and the one constant factor is change. It is impossible therefore to speak of any absolute law. The universe has evolved by means of chance variations, and no law has any ultimacy or absolute truth. As a result when we talk about law, we are talking about social customs or mores and about statistical averages. Social customs change, and what was law to the ancient Gauls is not law to the modern Frenchmen. We can expect men's ideas of law to change as their societies change and evolve. Moreover, statistics give us an average and a mean which determine normality, and our ideas of law are governed by what is customary and socially accepted.

In the name of speed, Morse and Vail had realized that they could save strokes by reserving the shorter sequences of dots and dashes for the most common letters. But which letters would be used most often? Little was known about the alphabet’s statistics. In search of data on the letters’ relative frequencies, Vail was inspired to visit the local newspaper office in Morristown, New Jersey, and look over the type cases. He found a stock of twelve thousand E’s, nine thousand T’s, and only two hundred Z’s. He and Morse rearranged the alphabet accordingly. They had originally used dash-dash-dot to represent T, the second most common letter; now they promoted T to a single dash, thus saving telegraph operators uncountable billions of key taps in the world to come. Long afterward, information theorists calculated that they had come within 15 percent of an optimal arrangement for telegraphing English text.

Baseball also has statistical rigor. Its gurus have an immense data set at hand, almost all of it directly related to the performance of players in the game. Moreover, their data is highly relevant to the outcomes they are trying to predict. This may sound obvious, but as we’ll see throughout this book, the folks building WMDs routinely lack data for the behaviors they’re most interested in. So they substitute stand-in data, or proxies. They draw statistical correlations between a person’s zip code or language patterns and her potential to pay back a loan or handle a job. These correlations are discriminatory, and some of them are illegal.

All of this, I believe, indicates that in order to grasp the basic grammar of the world, we need to merge three basic ingredients, not just two: not just general relativity and quantum mechanics, but also the theory of heat, that is, statistical mechanics and thermodynamics, which we can also describe as “information theory.

If socialist regimes work together, trade together, fight together, collaborate, and have fundamentally equivalent ideologies and tactics, they are genealogically related (a sort of Communist-Nazi brotherhood), which could be regarded as a Fascist-Marxist mindset. Of course, these socialist ideologues also fight each like rival siblings

The mind is more comfortable in reckoning probabilities in terms of the relative frequency of remembered or imagined events. That can make recent and memorable events - a plane crash, a shark attack, an anthrax infection - loom larger on one's worry list than more frequent and boring events, such as the car crashes and ladder falls that get printed beneath the fold on page B14. And it can lead risk experts to speak one language and ordinary people to hear another. In hearings for a proposed nuclear waste site, an expert might present a fault tree that lays out the conceivable sequences of events by which radioactivity might escape. For example, erosion, cracks in the bedrock, accidental drilling, or improper sealing might cause the release of radioactivity into groundwater. In turn, groundwater movement, volcanic activity, or an impact of a large meteorite might cause the release of radioactive wastes into the biosphere. Each train of events can be assigned a probability, and the aggregate probability of an accident from all the causes can be estimated. When people hear these analyses, however, the are not reassured but become more fearful than ever. They hadn't realized there are so many ways for something to go wrong! They mentally tabulate the number of disaster scenarios, rather than mentally aggregating the probabilities of the disaster scenarios.

Most people believed, correctly, that most normal North Africans tended to be relatively poor and therefore unlikely to be able to afford a new car, and on the basis of that statistical association their presumption was that the individual North African driver of a nice car was a criminal. Now they assume he is an Uber driver, which is clear progress.

Even in recent times, the empirical evidence does not support the claim that trade liberalization or incentive neutrality leads to faster growth. It is true that higher manufacturing growth rates have been typically associated with higher export growth rates (mostly in countries where export and import shares to GDP grew), but there is no statistical relation between either of these growth rates or degree of trade restrictions. Rather, almost all of successful export-oriented growth has come with selective trade and industrialization policies. In this regard, stable exchange rates and national price levels seem to be considerably more important than import policy in producing successful export-oriented growth

Disruption of identity characterized by two or more distinct personality states, which may be described in some cultures as an experience of possession. The disruption in identity involves marked discontinuity in sense of self and sense of agency, accompanied by related alterations in affect, behavior, consciousness, memory, perception, cognition, and/or sensory-motor functioning.

A total of 105 patrol officers died on the job in 2012. Less half of those (51) died as the result of violence, and another 48 died in traffic accidents. Between 1961 and 2012, 3,847 cops were murdered and 2,946 died in accidents—averaging about 75 murders and 58 fatal accidents in a typical year. Naturally it is not to be lost sight of that these numbers represent human lives, not widgets or sacks of potatoes. But let’s also remember that there were 4,383 fatal work injuries in 2012. As dangerous professions go, according to the Bureau of Labor Statistics, policing is not even in the top ten. In terms of total fatalities, more truck drivers are killed than any other kind of worker (741 in 2012). A better measure of occupational risk, however, is the rate of work-related deaths per 100,000 workers. In 2012, for example, it was 17.4 for truck drivers. At 15.0 deaths per 100,000, policing is slightly less dangerous than being a maintenance worker (15.7) and slightly more dangerous than supervising the gardener (14.7). The highest rate of fatalities is among loggers at 127.8 per 100,000, just ahead of fishers at 117.0. The rate for all occupations, taken together, is 3.2 per 100,000 workers. Where are the headlines, the memorials, the honor guards, and the sorrowful renderings of Taps for these workers? Where are the mayoral speeches, the newspaper editorials, the sober reflections that these brave men and women died, and that others risk their lives daily, so that we might continue to enjoy the benefits of modern society?

To be sure, it would be a mistake to underestimate the importance of the intuitive knowledge that everyone acquires about contemporary wealth and income levels, even in the absence of any theoretical framework or statistical analysis. Film and literature, nineteenth-century novels especially, are full of detailed information about the relative wealth and living standards of different social groups, and especially about the deep structure of inequality, the way it is justified, and its impact on individual lives. Indeed, the novels of Jane Austen and Honoré de Balzac paint striking portraits of the distribution of wealth in Britain and France between 1790 and 1830. Both novelists were intimately acquainted with the hierarchy of wealth in their respective societies.

The economic effects of minimum wage legislation have been analyzed in numerous statistical studies.[44] While there is a debate over the magnitude of the effects, the weight of research by academic scholars points to the conclusion that unemployment for some population groups is directly related to legal minimum wages and that the unemployment effects of the minimum wage law are felt disproportionately by nonwhites.

What was all this? He knew only too well. The statistical method! Probability theory! There was a greater probability of finding enemies among people of a non-proletarian background. And it was on these same grounds – probability theory – that the German Fascists had destroyed whole peoples and nations. The principle was inhuman, blind and inhuman. There was only one acceptable way of relating to people – a human way.

In the name of speed, Morse and Vail had realized that they could save strokes by reserving the shorter sequences of dots and dashes for the most common letters. But which letters would be used most often? Little was known about the alphabet’s statistics. In search of data on the letters’ relative frequencies, Vail was inspired to visit the local newspaper office in Morristown, New Jersey, and look over the type cases.

Whatever the evolutionary precursors of drug use are, a permanently “drug-free” human culture has yet to be discovered. Like music, language, art, and tool use, the pursuit of altered states of consciousness is a human universal. With access to few alternatives, Siberian shamans imbibe reindeer and human urine to maximize the psychedelic yield of Amanita muscaria mushrooms (the metabolite that is excreted may be stronger than the substance initially ingested); on nearly the opposite side of the world, New Zealanders party with untested “research chemicals” synthesized by Chinese chemists. Drug use spans time and culture. It is a rare human who has never taken a drug to alter her mood; statistically, it is non-users who are abnormal. Indeed, today, around two thirds of Americans over 12 have had at least one drink in the last year, and 1 in 5 are current smokers. (In the 1940s and ’50s, a whopping 67% of men smoked.) Among people ages 21 to 25, 60% have taken an illegal drug at least once—overwhelmingly marijuana—and 20% have taken one in the past month. Moreover, around half of us could suffer from physical withdrawal symptoms if denied our daily coffee. While Americans are relatively prodigious drug users—topping the charts in the use of many substances—we are far from alone in our psychoactive predilections.

Monarchs have a great weakness, however, for their own sons, no matter how feckless and inept. A statistical study should be done across cultures assessing the relative frequency of the bizarre outcomes to which monarchical succession is prone: failure to provide an heir or successor, provision of an heir completely inept, or division of rule among several incompatible ones. Orderly succession followed by a successful reign is the exception.

In 7.81 square miles of vaunted black community, the 850 square feet of Dum Dum Donuts was the only place in the "community" where one could experience the Latin root of the word, where a citizen could revel in common togetherness. So one rainy Sunday afternoon, not long after the tanks and media attention had left, my father ordered his usual. He sat at the table nearest the ATM and said aloud, to no one in particular, "Do you know that the average household net worth for whites is $113,149 per year, Hispanics $6,325, and black folks $5,677?" "For real?" "What's your source material, nigger?" "The Pew Research Center." Motherfuckers from Harvard to Harlem respect the Pew Research Center, and hearing this, the concerned patrons turned around in their squeaky plastic seats as best they could, given that donut shop swivel chairs swivel only six degrees in either direction. Pops politely asked the manager to dim the lights. I switched on the overhead projector, slid a transparency over the glass, and together we craned our necks toward the ceiling, where a bar graph titled "Income Disparity as Determined by Race" hovered overhead like some dark, damning, statistical cumulonimbus cloud threatening to rain on our collective parades. "I was wondering what that li'l nigger was doing in a donut shop with a damn overhead projector.

The starting point of Darwin's theory of evolution is precisely the existence of those differences between individual members of a race or species which morphologists for the most part rightly neglect. The first condition necessary, in order that any process of Natural Selection may begin among a race, or species, is the existence of differences among its members; and the first step in an enquiry into the possible effect of a selective process upon any character of a race must be an estimate of the frequency with which individuals, exhibiting any given degree of abnormality with respect to that, character, occur. The unit, with which such an enquiry must deal, is not an individual but a race, or a statistically representative sample of a race; and the result must take the form of a numerical statement, showing the relative frequency with which the various kinds of individuals composing the race occur.

There is indeed a fundamental beauty in mathematical abstractions. They so attracted the Greek philosopher Plato that he declared that all those things that we can see and touch are, in fact, mere shadows of the true reality and that the real things of this universe can be found only through the use of pure reason. Plato's knowledge of mathematics was relatively naive, and many of the cherished purities of Greek mathematics have been shown to be flawed.

The associative machinery seeks causes. The difficulty we have with statistical regularities is that they call for a different approach. Instead of focusing on how the event at hand came to be, the statistical view relates it to what could have happened instead. Nothing in particular caused it to be what it is—chance selected it from among its alternatives. Our predilection for causal thinking exposes us to serious mistakes in evaluating the randomness of truly random events.

Recently a group of researchers conducted a computer analysis of three decades of hit songs. The researchers reported a statistically significant trend toward narcissism and hostility in popular music. In line with their hypothesis, they found a decrease in usages such as we and us and an increase in I and me. The researchers also reported a decline in words related to social connection and positive emotions, and an increase in words related to anger and antisocial behavior, such as hate or kill.

The Chicago Commission on Race Relations found evidence of systemic profiling, abuse, and corruption. Officials testified that officers routinely arrested blacks on suspicion and brought them “into court without a bit of evidence of any offense.” A former chief of police admitted that black migrants “naturally” attracted “greater suspicion than would attach to the white man.” Such startling testimony proved that police bias and discrimination were baked into the arrest statistics, leading the commissioners to abandon

One of the most telling statistics regarding multiples is that 97 percent of them have had a history of severe childhood trauma, often in the form of monstrous psychological, physical, and sexual abuse. This has led many researchers to conclude that becoming a multiple is the psyche's way of coping with extraordinary and soul-crushing pain. By dividing up into one or more personalities the psyche is able to parcel out the pain, in a way, and have several personalities bear what would be too much for just one personality to withstand. In this sense becoming a multiple may be the ultimate example of what Bohm means by fragmentation. It is interesting to note that when the psyche fragments itself, it does not become a collection of broken and jagged-edged shards, but a collection of smaller wholes, complete and self-sustaining with their own traits, motives, and desires. Although these wholes are not identical copies of the original personality, they are related to the dynamics of the original personality, and this in itself suggests that some kind of holographic process is involved.

The universe, it appeared, had never been kind to Captain Bortrek, conspiring against him in a fashion that Threepio privately considered unlikely given the man's relative unimportance. Knowing what he did about the Alderaan social structure, shipping regulations, the psychology of law enforcement agents, and the statistical behavior patterns of human females, Threepio was much inclined to doubt that so many hundreds of people would spend that much time thinking up ways to thwart and injure a small-time free-trader who was, by his own assertion, only trying to make a living.

Working on my Ph.D. at the University of Wyoming, I was required to take an advanced statistics course. I had completed the beginning courses several years earlier, but could remember very little. I had no idea how I was going to manage the requirements of an advanced class. Several weeks into the semester, I was floundering. I approached the chair of my committee, Louise Jackson, and said, “This is really over my head. Usually I at least know enough about a subject to follow along. This time I am totally lost.” “Good!” she said. “You don’t know how happy that news makes me.” Her response took me totally by surprise. Teachers are not usually glad when you announce that you are failing. Dr. Jackson continued: “Remember how this feels. Memorize this moment. Don’t ever forget this lesson. This is how many of your future students will feel, and you must be able to relate to them in order to understand and be effective in helping them.” She then gave me some suggestions, including the names of a few possible tutors. She also arranged to meet with me regularly to review my progress—things she assured me she would never have done had she not also once struggled through a few difficult classes of her own.

Are the religious individuals in a society more moral than the secular ones? Many researchers have looked into this, and the main finding is that there are few interesting findings. There are subtle effects here and there: some studies find, for instance, that the religious are slightly more prejudiced, but this effect is weak when one factors out other considerations, such as age and political attitudes, and exists only when religious belief is measured in certain ways. The only large effect is that religious Americans give more to charity (including nonreligious charities) than atheists do. This holds even when one controls for demographics (religious Americans are more likely than average to be older, female, southern, and African American). To explore why this relationship exists, the political scientists Robert Putnam and David Campbell asked people about life after death, the importance of God to morality, and various other facets of religious belief. It turns out that none of their answers to such questions were related to behaviors having to do with volunteering and charitable giving. Rather, participation in the religious community was everything. As Putnam and Campbell put it, “Once we know how observant a person is in terms of church attendance, nothing that we can discover about the content of her religious faith adds anything to our understanding or prediction of her good neighborliness.… In fact, the statistics suggest that even an atheist who happened to become involved in the social life of the congregation (perhaps through a spouse) is much more likely to volunteer in a soup kitchen than the most fervent believer who prays alone. It is religious belongingness that matters for neighborliness, not religious believing.” This importance of community, and the irrelevance of belief, extends as well to the nastier effects of religion. The psychologist Jeremy Ginges and his colleagues found a strong relationship between religiosity and support for suicide bombing among Palestinian Muslims, and, again, the key factor was religious community, not religious belief: mosque attendance predicted support for suicide attacks; frequency of prayer did not. Among Indonesian Muslims, Mexican Catholics, British Protestants, Russian Orthodox in Russia, Israeli Jews, and Indian Hindus, frequency of religious attendance (but again, not frequency of prayer) predicts responses to questions such as “I blame people of other religions for much of the trouble in this world.

But our Edenic tent–God doesn’t just want to save us. He actually wants to be with us. He doesn’t just love us. God actually likes us. So God removes His royal robes and steps down from His throne to experience—for the first time—what it is like to be human. God is omniscient, which means that He is all-knowing. There’s nothing in the universe, no piece of information, no fact, no statistic that He doesn’t know. The hairs on your head, the zits on your face—He knows about every one. But until the incarnation, God hadn’t experienced human nature. Since zits aren’t a sin, perhaps Jesus had them too. God knows every hair on your head, but through the incarnation, God knows what it feels like to have hair ripped out. God knows about tiredness, but through the incarnation, He experiences exhaustion. God knows how many molecules it takes to shoot a hunger pain from your stomach to your brain. But through the incarnation, God knows what it feels like to starve to the point of death. Through the incarnation, God has enjoyed the same warm wave of sunlight that splashes across your face on the first day of spring. When you bathe in it, God smiles because He’s bathed in it too. He’s been refreshed by a night’s sleep after a long day of work. Warmed by a toasty bed on a cold winter night. Enjoyed a rich glass of wine while celebrating among friends. God authored creation. But through the incarnation, God experienced creation. And He encountered joy under the bridge. He also experienced pain. Relational, psychological, emotional, and physical agony. God has suffered the misery and brokenness of the same sin-saturated world that oppresses us every day. The pain of being rejected, beaten, abused, unloved, uncared for, mocked, shamed, spat upon, and disrespected as an image bearer of the Creator. Jesus knows all of this. He’s experienced all of this. And He willingly endured it to bring you back to Eden.

1. Understanding key ideas. I recently read an article in the Economist on declining marriage rates among women in Asia. I had no immediate use for the detailed statistics in that article, but I thought I might use them in the future to describe how demographic trends affect public retirement plans. So I skimmed it to learn the general trends. 2. Finding specific facts. At the opposite pole is reading closely for facts. When I’m preparing for a board meeting, I carefully look over the memos and reports related to the company’s quarterly performance. I want to be able to remember certain key statistics and substantive points to discuss with the board.

The habit of thinking about progress as "development" has meant that many aspects of the environment were simply neglected. With the stereotype of "progress" before their eyes, Americans have in the mass seen little that did not accord with that progress. They saw the expansion of cities, but not the accretion of slums; they cheered the census statistics, but refused to consider overcrowding; they pointed with pride to their growth, bu would not see the drift from the land, or the unassimilated immigration. They expanded industry furiously at reckless cost to their natural resources; they built up gigantic corporations without arranging for industrial relations. They grew to be one of the most powerful nations on earth without preparing their institutions or their minds for the ending of their isolation... There comes a time, therefore, when the blind spots come from the edge of vision into the center. Then unless there are critics who have the courage to sound an alarm, and leaders capable of understanding the change, and a people tolerant by habit, the stereotype, instead of economizing effort, and focussing energy as it did in 1917 and 1918, may frustrate effort and waste men's energy by blinding them, as it did for those people who cried for a Carthaginian peace in 1919 and deplored the Treaty of Versailles in 1921.

These statues have a complex history. They were not erected to honor the Confederate dead following the war or even at the end of Reconstruction. Most appeared in the early 1920s to send a message that the race-relation liberalization that happened between 1880 and 1900 would not return. The progress and normalcy would be replaced by a racist/statist/“progressive” movement rallying around new eugenic laws, zoning, white supremacy, forced exclusion, state segregation and so on—policies supported not by the people but by white elites infected with demographic fear and pseudo-science. This is when a movement started putting up these statues, not to honor history but as a symbol of intimidation and state control of association.

Effort is required to maintain simultaneously in memory several ideas that require separate actions, or that need to be combined according to a rule—rehearsing your shopping list as you enter the supermarket, choosing between the fish and the veal at a restaurant, or combining a surprising result from a survey with the information that the sample was small, for example. System 2 is the only one that can follow rules, compare objects on several attributes, and make deliberate choices between options. The automatic System 1 does not have these capabilities. System 1 detects simple relations (“they are all alike,” “the son is much taller than the father”) and excels at integrating information about one thing, but it does not deal with multiple distinct topics at once, nor is it adept at using purely statistical information.

This irrelevance of molecular arrangements for macroscopic results has given rise to the tendency to confine physics and chemistry to the study of homogeneous systems as well as homogeneous classes. In statistical mechanics a great deal of labor is in fact spent on showing that homogeneous systems and homogeneous classes are closely related and to a considerable extent interchangeable concepts of theoretical analysis (Gibbs theory). Naturally, this is not an accident. The methods of physics and chemistry are ideally suited for dealing with homogeneous classes with their interchangeable components. But experience shows that the objects of biology are radically inhomogeneous both as systems (structurally) and as classes (generically). Therefore, the method of biology and, consequently, its results will differ widely from the method and results of physical science.

There was a time when the public had an unquestionable faith in biomedicine and the practitioners who translated it into everyday patient care—and physicians believed that the public's trust was justified based on their educational qualifications and training. But today, many patients believe that individual clinicians must earn their trust, just as a close relative has earned it through shared experience. ...Gallop polling over the last several decades that demonstrates how much the public's confidence in most US institutions has deteriorated. Confidence in the medical system in particular fell from 80% in 1975 to 37% in 2015. Statistics from the General Social Survey confirm this troubling trend. Baron and Berinsky explain the historical reasons for this shift in attitudes, but the more pressing question is: How can individual clinicians, and the profession as a whole, regain the patients' trust? 

To counter all these biases, both in my readers, and in myself, I try to move my estimates in the following directions. I try to be less confident, to expect typical outcomes to be more ordinary, but also to expect more deviations from typical outcomes. I try to rely more on ordinary methods, sources, and assumptions, and also more on statistics or related systems and events. I expect bigger deviations from traditional images of the future, but also rely less on strange, exotic, unlikely-seeming, and hypothetical possibilities. Looking backward, future folk should see their world as changing less from their past than we might see looking forward. Seen up close and honestly, I expect the future usually to look like most places: mundane, uninspiring, and morally ambiguous, with grand hopes and justifications often masking lives of quiet desperation. Of course, lives of quiet desperation can still be worth living.

For it is true historically that those who have shown the greatest subtlety with language have shown the greatest power to understand (this does not exclude Sophists, for Plato made the point that one must be able to see the truth accurately in order to judge one’s distance from it if he is practicing deception). To take a contemporary example which has statistical support: American universities have found that with few exceptions students who display the greatest mastery of words, as evidenced by vocabulary tests and exercises in writing, make the best scholastic records regardless of the department of study they enter. For physics, for chemistry, for engineering—it matters not how superficially unrelated to language the branch of study may be—command of language will prognosticate aptitude. Facility with words bespeaks a capacity to learn relations and grasp concepts; it is a means of access to the complex reality. Evidently

Beauty is not the goal of competitive sports, but high-level sports are a prime venue for the expression of human beauty. The relation is roughly that of courage to war. The human beauty we’re talking about here is beauty of a particular type; it might be called kinetic beauty. Its power and appeal are universal. It has nothing to do with sex or cultural norms. What it seems to have to do with, really, is human beings’ reconciliation with the fact of having a body. Of course, in men’s sports no one ever talks about beauty or grace or the body. Men may profess their “love” of sports, but that love must always be cast and enacted in the symbology of war: elimination vs. advance, hierarchy of rank and standing, obsessive statistics, technical analysis, tribal and/or nationalist fervor, uniforms, mass noise, banners, chest-thumping, face-painting, etc. For reasons that are not well understood, war’s codes are safer for most of us than love’s." - from "Federer Both Flesh and Not

Search engine query data is not the product of a designed statistical experiment and finding a way to meaningfully analyse such data and extract useful knowledge is a new and challenging field that would benefit from collaboration. For the 2012–13 flu season, Google made significant changes to its algorithms and started to use a relatively new mathematical technique called Elasticnet, which provides a rigorous means of selecting and reducing the number of predictors required. In 2011, Google launched a similar program for tracking Dengue fever, but they are no longer publishing predictions and, in 2015, Google Flu Trends was withdrawn. They are, however, now sharing their data with academic researchers... Google Flu Trends, one of the earlier attempts at using big data for epidemic prediction, provided useful insights to researchers who came after them... The Delphi Research Group at Carnegie Mellon University won the CDC’s challenge to ‘Predict the Flu’ in both 2014–15 and 2015–16 for the most accurate forecasters. The group successfully used data from Google, Twitter, and Wikipedia for monitoring flu outbreaks.

Nobody as yet had really acknowledged to himself what the disease connoted. Most people were chiefly aware of what ruffled the normal tenor of their lives or affected their interests. They were worried and irritated—but these are not feelings with which to confront plague. Their first reaction, for instance, was to abuse the authorities. The Prefect’s riposte to criticisms echoed by the press—Could not the regulations be modified and made less stringent?—was somewhat unexpected. Hitherto neither the newspapers nor the Ransdoc Information Bureau had been given any official statistics relating to the epidemic. Now the Prefect supplied them daily to the bureau, with the request that they should be broadcast once a week. In this, too, the reaction of the public was slower than might have been expected. Thus the bare statement that three hundred and two deaths had taken place in the third week of plague failed to strike their imagination. For one thing, all the three hundred and two deaths might not have been due to plague. Also, no one in the town had any idea of the average weekly death-rate in ordinary times. The population of the town was about two hundred thousand. There was no knowing if the present death-rate were really so abnormal. This is, in fact, the kind of statistics that nobody ever troubles much about—notwithstanding that its interest is obvious. The public lacked, in short, standards of comparison. It was only as time passed and the steady rise in the death-rate could not be ignored that public opinion became alive to the truth. For in the fifth week there were three hundred and twenty-one deaths, and three hundred and forty-five in the sixth. These figures, anyhow, spoke for themselves. Yet they were still not sensational enough to prevent our townsfolk, perturbed though they were, from persisting in the idea that what was happening was a sort of accident, disagreeable enough, but certainly of a temporary order. So they went on strolling about the town as usual and sitting at the tables on café terraces. Generally speaking, they did not lack courage, bandied more jokes than lamentations, and made a show of accepting cheerfully unpleasantnesses that obviously could be only passing. In short, they kept up appearances.

The process of simplifying man's environment and rendering it increasingly elemental and crude has a cultural as well as a physical dimension. The need to manipulate immense urban populations—to transport, feed, employ, educate and somehow entertain millions of densely concentrated people—leads to a crucial decline in civic and social standards. A mass concept of human relations—totalitarian, centralistic and regimented in orientation—tends to dominate the more individuated concepts of the past. Bureaucratic techniques of social management tend to replace humanistic approaches. All that is spontaneous, creative and individuated is circumscribed by the standardized, the regulated and the massified. The space of the individual is steadily narrowed by restrictions imposed upon him by a faceless, impersonal social apparatus. Any recognition of unique personal qualities is increasingly surrendered to the manipulation of the lowest common denominator of the mass. A quantitative, statistical approach, a beehive manner of dealing with man, tends to triumph over the precious individualized and qualitative approach which places the strongest emphasis on personal uniqueness, free expression and cultural complexity.

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.

I must at this point reiterate my strong objection to being asked to fill in forms in which I have to tick a box labelling my 'race' or 'ethnicity', and voice my strong support for Lewontin's statement that racial classification can be actively destructive of social and human relations - especially when people use racial classification as a way of treating people differently, whether through negative or positive discrimination. To tie a racial label to somebody is informative in the sense that it tells you more than one thing about them. It might reduce your uncertainty about the colour of their hair, the colour of their skin, the straightness of their hair, the shape of their eye, the shape of their nose and how tall they are. But there is no reason to suppose that it tells you anything about how well-qualified they are for a job. And even in the unlikely event that it did reduce your statistical uncertainty about their likely suitability for some particular job, it would still be wicked to use racial labels as a basis for discrimination when hiring somebody. Choose on the basis of ability, and if, having done so, you end up with an all-black sprinting team, so be it. You have not practised racial discrimination in arriving at this conclusion

HUNGER AND OBESITY The change in diets around the world is also creating a global obesity epidemic—and in its wake a global diabetes epidemic—even as more than 900 million people in the world still suffer from chronic hunger. In the United States, where many global trends begin, the weight of the average American has increased by approximately twenty pounds in the last forty years. A recent study projects that half the adult population of the United States will be obese by 2030, with one quarter of them “severely obese.” At a time when hunger and malnutrition are continuing at still grossly unacceptable levels in poor countries around the world (and in some pockets within developed countries), few have missed the irony that simultaneously obesity is at record levels in developed countries and growing in many developing countries. How could this be? Well, first of all, it is encouraging to note that the world community has been slowly but steadily decreasing the number of people suffering from chronic hunger. Secondly, on a global basis, obesity has more than doubled in the last thirty years. According to the World Health Organization, almost 1.5 billion adults above the age of twenty are overweight, and more than a third of them are classified as obese. Two thirds of the world’s population now live in countries where more people die from conditions related to being obese and overweight than from conditions related to being underweight. Obesity represents a major risk factor for the world’s leading cause of death—cardiovascular diseases, principally heart disease and stroke—and is the major risk factor for diabetes, which has now become the first global pandemic involving a noncommunicable disease.* Adults with diabetes are two to four times more likely to suffer heart disease or a stroke, and approximately two thirds of those suffering from diabetes die from either stroke or heart disease.† The tragic increase in obesity among children is particularly troubling; almost 17 percent of U.S. children are obese today, as are almost 7 percent of all children in the world. One respected study indicates that 77 percent of obese children will suffer from obesity as adults. If there is any good news in the latest statistics, it is that the prevalence of obesity in the U.S. appears to be reaching a plateau, though the increases in childhood obesity ensure that the epidemic will continue to grow in the future, both in the U.S. and globally. The causes of this surge in obesity are both simple—in that people are eating too much and exercising

We’ve become so focused as a society on the question of whether a given sexual behavior is evolutionarily “natural” or “unnatural” that we’ve lost sight of the more important question: Is it harmful? In many ways, it’s an even more challenging question, because although naturalness can be assessed by relatively straightforward queries about statistical averages—for example, “How frequently does it appear in other species?” and “In what percentage of the human population does it occur?”—the experience of harm is largely subjective. As such, it defies such direct analyses and requires definitions that resonate with people in vastly different ways. When it comes to sexual harm in particular, what’s harmful to one person not only is completely harmless to another but may even, believe it or not, be helpful or positive. If the supermodel Kate Upton were to walk into my office right now and tie me to my chair before doing a slow striptease and depositing her vagina in my face, I think I’d require therapy for years. But if this identical event were to happen to my heterosexual brother or to one of my lesbian friends, I suspect their brains would process such a “tragic” experience very differently. (And that of my not-very-amused sister-in-law would see my brother’s encounter with said vagina differently still.)

I must at this point reiterate my strong objection to being asked to fill in forms in which I have to tick a box labelling my 'race' or 'ethnicity', and voice my strong support for Lewontin's statement that racial classification can be actively destructive of social and human relations - especially when people use racial classification as a way of treating people differently, whether through negative or positive discrimination. To tie a racial label to somebody is informative in the sense that it tells you more than one thing about them. It might reduce your uncertainty about the colour of their hair, the colour of their skin, the straightness of their hair, the shape of their eye, the shape of their nose and how tall they are. But there is no reason to suppose that it tells you anything about how well-qualified they are for a job. And even in the unlikely event that it did reduce your statistical uncertainty about their likely suitability for some particular job, it would still be wicked to use racial labels as a basis for discrimination when hiring somebody. Choose on the basis of ability, and if, having done so, you end up with an all-black sprinting team, so be it. You have not practised racial discrimination in arriving at this conclusion... Discriminating against individuals purely on the basis of a group to which they belong is, I am inclined to think, always evil. There is near-universal agreement today that the apartheid laws of South Africa were evil. Positive discrimination in favour of 'minority' students on American campuses can fairly, in my opinion, be attacked on the same grounds as apartheid. Both treat people as representative of groups rather than as individuals in their own right. Positive discrimination is sometimes justified as redressing centuries of injustice. But how can it be just to pay back a single individual today for the wrongs done by long-dead members of a plural group to which he belongs?

The Delusion of Lasting Success promises that building an enduring company is not only achievable but a worthwhile objective. Yet companies that have outperformed the market for long periods of time are not just rare, they are statistical artifacts that are observable only in retrospect. Companies that achieved lasting success may be best understood as having strung together many short-term successes. Pursuing a dream of enduring greatness may divert attention from the pressing need to win immediate battles. The Delusion of Absolute Performance diverts our attention from the fact that success and failure always take place in a competitive environment. It may be comforting to believe that our success is entirely up to us, but as the example of Kmart demonstrated, a company can improve in absolute terms and still fall further behind in relative terms. Success in business means doing things better than rivals, not just doing things well. Believing that performance is absolute can cause us to take our eye off rivals and to avoid decisions that, while risky, may be essential for survival given the particular context of our industry and its competitive dynamics. The Delusion of the Wrong End of the Stick lets us confuse causes and effects, actions and outcomes. We may look at a handful of extraordinarily successful companies and imagine that doing what they did can lead to success — when it might in fact lead mainly to higher volatility and a lower overall chance of success. Unless we start with the full population of companies and examine what they all did — and how they all fared — we have an incomplete and indeed biased set of information. The Delusion of Organizational Physics implies that the business world offers predictable results, that it conforms to precise laws. It fuels a belief that a given set of actions can work in all settings and ignores the need to adapt to different conditions: intensity of competition, rate of growth, size of competitors, market concentration, regulation, global dispersion of activities, and much more. Claiming that one approach can work everywhere, at all times, for all companies, has a simplistic appeal but doesn’t do justice to the complexities of business. These points, taken together, expose the principal fiction at the heart of so many business books — that a company can choose to be great, that following a few key steps will predictably lead to greatness, that its success is entirely of its own making and not dependent on factors outside its control.

Obama is also directing the U.S. government to invest billions of dollars in solar and wind energy. In addition, he is using bailout leverage to compel the Detroit auto companies to build small, “green” cars, even though no one in the government has investigated whether consumers are interested in buying small, “green” cars—the Obama administration just believes they should. All these measures, Obama recognizes, are expensive. The cap and trade legislation is estimated to impose an $850 billion burden on the private sector; together with other related measures, the environmental tab will exceed $1 trillion. This would undoubtedly impose a significant financial burden on an already-stressed economy. These measures are billed as necessary to combat global warming. Yet no one really knows if the globe is warming significantly or not, and no one really knows if human beings are the cause of the warming or not. For years people went along with Al Gore’s claim that “the earth has a fever,” a claim illustrated by misleading images of glaciers disappearing, oceans swelling, famines arising, and skies darkening. Apocalypse now! Now we know that the main body of data that provided the basis for these claims appears to have been faked. The Climategate scandal showed that scientists associated with the Intergovernmental Panel on Climate Change were quite willing to manipulate and even suppress data that did not conform to their ideological commitment to global warming.3 The fakers insist that even if you discount the fakery, the data still show.... But who’s in the mood to listen to them now? Independent scientists who have reviewed the facts say that average global temperatures have risen by around 1.3 degrees Fahrenheit in the past 100 years. Lots of things could have caused that. Besides, if you project further back, the record shows quite a bit of variation: periods of warming, followed by periods of cooling. There was a Medieval Warm Period around 1000 A.D., and a Little Ice Age that occurred several hundred years later. In the past century, the earth warmed slightly from 1900 to 1940, then cooled slightly until the late 1970s, and has resumed warming slightly since then. How about in the past decade or so? Well, if you count from 1998, the earth has cooled in the past dozen years. But the statistic is misleading, since 1998 was an especially hot year. If you count from 1999, the earth has warmed in the intervening period. This statistic is equally misleading, because 1999 was a cool year. This doesn’t mean that temperature change is in the eye of the beholder. It means, in the words of Roy Spencer, former senior scientist for climate studies at NASA, that “all this temperature variability on a wide range of time scales reveals that just about the only thing constant in climate is change.”4

The society’s ‘look’ is a self-publicizing one. The American flag itself bears witness to this by its omnipresence, in fields and built-up areas, at service stations, and on graves in the cemeteries, not as a heroic sign, but as the trademark of a good brand. It is simply the label of the finest successful international enterprise, the US. This explains why the hyperrealists were able to paint it naively, without either irony or protest (Jim Dine in the sixties), in much the same way as Pop Art gleefully transposed the amazing banality of consumer goods on to its canvases. There is nothing here of the fierce parodying of the American anthem by Jimi Hendrix, merely the light irony and neutral humour of things that have become banal, the humour of the mobile home and the giant hamburger on the sixteen-foot long billboard, the pop and hyper humour so characteristic of the atmosphere of America, where things almost seem endowed with a certain indulgence towards their own banality. But they are indulgent towards their own craziness too. Looked at more generally, they do not lay claim to being extraordinary; they simply are extraordinary. They have that extravagance which makes up odd, everyday America. This oddness is not surrealistic (surrealism is an extravagance that is still aesthetic in nature and as such very European in inspiration); here, the extravagance has passed into things. Madness, which with us is subjective, has here become objective, and irony which is subjective with us has also turned into something objective. The fantasmagoria and excess which we locate in the mind and the mental faculties have passed into things themselves. Whatever the boredom, the hellish tedium of the everyday in the US or anywhere else, American banality will always be a thousand times more interesting than the European - and especially the French - variety. Perhaps because banality here is born of extreme distances, of the monotony of wide-open spaces and the radical absence of culture. It is a native flower here, asis the opposite extreme, that of speed and verticality, of an excess that verges on abandon, and indifference to values bordering on immorality, whereas French banality is a hangover from bourgeois everyday life, born out of a dying aristocratic culture and transmuted into petty-bourgeois mannerism as the bourgeoisie shrank away throughout the nineteenth century. This is the crux: it is the corpse of the bourgeoisie that separates us. With us, it is that class that is the carrier of the chromosome of banality, whereas the Americans have succeeded in preserving some humour in the material signs of manifest reality and wealth. This also explains why Europeans experience anything relating to statistics as tragic. They immediately read in them their individual failure and take refuge in a pained denunciation of the merely quantitative. The Americans, by contrast, see statistics as an optimistic stimulus, as representing the dimensions of their good fortune, their joyous membership of the majority. Theirs is the only country where quantity can be extolled without compunction.

PATTERNS OF THE “SHY” What else is common among people who identify themselves as “shy?” Below are the results of a survey that was administered to 150 of my program’s participants. The results of this informal survey reveal certain facts and attitudes common among the socially anxious. Let me point out that these are the subjective answers of the clients themselves—not the professional opinions of the therapists. The average length of time in the program for all who responded was eight months. The average age was twenty-eight. (Some of the answers are based on a scale of 1 to 5, 1 being the lowest.) -Most clients considered shyness to be a serious problem at some point in their lives. Almost everyone rated the seriousness of their problem at level 5, which makes sense, considering that all who responded were seeking help for their problem. -60 percent of the respondents said that “shyness” first became enough of a problem that it held them back from things they wanted during adolescence; 35 percent reported the problem began in childhood; and 5 percent said not until adulthood. This answer reveals when clients were first aware of social anxiety as an inhibiting force. -The respondents perceived the average degree of “sociability” of their parents was a 2.7, which translates to “fair”; 60 percent of the respondents reported that no other member of the family had a problem with “shyness”; and 40 percent said there was at least one other family member who had a problem with “shyness.” -50 percent were aware of rejection by their peers during childhood. -66 percent had physical symptoms of discomfort during social interaction that they believed were related to social anxiety. -55 percent reported that they had experienced panic attacks. -85 percent do not use any medication for anxiety; 15 percent do. -90 percent said they avoid opportunities to meet new people; 75 percent acknowledged that they often stay home because of social fears, rather than going out. -80 percent identified feelings of depression that they connected to social fears. -70 percent said they had difficulty with social skills. -75 percent felt that before they started the program it was impossible to control their social fears; 80 percent said they now believed it was possible to control their fears. -50 percent said they believed they might have a learning disability. -70 percent felt that they were “too dependent on their parents”; 75 percent felt their parents were overprotective; 50 percent reported that they would not have sought professional help if not for their parents’ urging. -10 percent of respondents were the only child in their families; 40 percent had one sibling; 30 percent had two siblings; 10 percent had three; and 10 percent had four or more. Experts can play many games with statistics. Of importance here are the general attitudes and patterns of a population of socially anxious individuals who were in a therapy program designed to combat their problem. Of primary significance is the high percentage of people who first thought that “shyness” was uncontrollable, but then later changed their minds, once they realized that anxiety is a habit that can be broken—without medication. Also significant is that 50 percent of the participants recognized that their parents were the catalyst for their seeking help. Consider these statistics and think about where you fit into them. Do you identify with this profile? Look back on it in the coming months and examine the ways in which your sociability changes. Give yourself credit for successful breakthroughs, and keep in mind that you are not alone!

Let’s zoom in on a particular form of synesthesia as an example. For most of us, February and Wednesday do not have any particular place in space. But some synesthetes experience precise locations in relation to their bodies for numbers, time units, and other concepts involving sequence or ordinality. They can point to the spot where the number 32 is, where December floats, or where the year 1966 lies.8 These objectified three-dimensional sequences are commonly called number forms, although more precisely the phenomenon is called spatial sequence synesthesia.9 The most common types of spatial sequence synesthesia involve days of the week, months of the year, the counting integers, or years grouped by decade. In addition to these common types, researchers have encountered spatial configurations for shoe and clothing sizes, baseball statistics, historical eras, salaries, TV channels, temperature, and more.

In the past decade, the historically consistent division in the United States between the share of total national income going to labor and that going to physical capital seems to have changed significantly. As the economists Susan Fleck, John Glaser, and Shawn Sprague noted in the U.S. Bureau of Labor Statistics’ Monthly Labor Review in 2011, “Labor share averaged 64.3 percent from 1947 to 2000. Labor share has declined over the past decade, falling to its lowest point in the third quarter of 2010, 57.8 percent.” Recent moves to “re-shore” production from overseas, including Apple’s decision to produce its new Mac Pro computer in Texas, will do little to reverse this trend. For in order to be economically viable, these new domestic manufacturing facilities will need to be highly automated. Other countries are witnessing similar trends. The economists Loukas Karabarbounis and Brent Neiman have documented significant declines in labor’s share of GDP in 42 of the 59 countries they studied, including China, India, and Mexico. In describing their findings, Karabarbounis and Neiman are explicit that progress in digital technologies is an important driver of this phenomenon: “The decrease in the relative price of investment goods, often attributed to advances in information technology and the computer age, induced firms to shift away from labor and toward capital. The lower price of investment goods explains roughly half of the observed decline in the labor share.

It is a scandal—or, rather, it should be a scandal and one wonders why it isn’t—that the US prison population, after reaching a postwar low in the early 1970s, has since grown more than 500 percent. The United States locks up a higher percentage of its own population than any other nation in the world. Even with extraordinary prison construction projects over the last decades, the cells are still overfull. This massive expansion cannot be explained by a growing criminality of the US population or the enhanced efficiency of law enforcement. In fact, US crime rates in this period have remained relatively constant. The scandal of US prison expansion is even more dramatic when one observes how it operates along race divisions. Latinos are incarcerated at a rate almost double that of whites, and African Americans at a rate almost six times as high. The racial imbalance of those on death row is even more extreme. It is not hard to find shocking statistics. One in eight black US males in their twenties, for instance, is in jail or prison on any given day. The number of African Americans under correctional control today, Michelle Alexander points out, is greater than the number of slaves in the mid-nineteenth century. Some authors refer to the racially skewed prison expansion as a return to elements of the plantation system or the institution of new Jim Crow laws. Keep in mind that this differential racial pattern of imprisonment is not isolated to the United States. In Europe and elsewhere, if one considers immigrant detention centers and refugee camps as arms of the carceral apparatus, those with darker skin are disproportionately in captivity.

The Effects of a Low-Carbohydrate Ketogenic Diet and a Low-Fat Diet on Mood, Hunger, and Other Self-Reported Symptoms [25]. In this trial 59 low carb dieters lost 12.9kg or 28.4lbs over 6 months, and low fat dieters lost 6.7kg or 14.7lbs over 6 months. Although the low carb dieters lost almost twice as much weight they had statistically significant less hunger than the low fat dieters,

Helliwell and his team have run several iterations of the World Values Survey and the Gallup World Poll through their statistical grinders and have found that when it comes to life satisfaction, relationships with other people beat income, hands down. For example, these polls asked people if they had a friend or relative to count on when needed. Just going from being friendless to having one friend or family member to confide in had the same effect on life satisfaction as a tripling of income.

State social spending is taken to be the normal case and if ever questioned is done so only in relation to private charity; which is to say, it is generally assumed charity of some sort is necessary; the state is better suited to this than private individuals. The idea no one in present society should be dependent on any sort of charity, public or private, in present society is, of course, dismissed as utopian and, not surprisingly, often by the same sorts of folks as are “outraged” by statistics on concentration of wealth that circulate in the media.

When I look at the statistics in more vulnerability-intolerant Viking-or-Victim professions, I see a dangerous pattern developing. And no place is this more evident than in the military. The statistics on post-traumatic-stress-related suicides, violence, addiction, and risk-taking all point to this haunting truth: For soldiers serving in Afghanistan and Iraq, coming home is more lethal than being in combat. From the invasion of Afghanistan to the summer of 2009, the US military lost 761 soldiers in combat in that country. Compare that to the 817 who took their own lives over the same period. And this number doesn’t account for deaths related to violence, high-risk behaviors, and addiction.

The attack on 9/11 was a localized event, affecting only a relatively small number of Americans. As indicated earlier, the general threat of terrorism, even factoring in the large death toll on that tragic day, produces a statistically insignificant threat to the average person’s life. People across the country, however, were gripped with fear. And because we are an object-oriented people, most felt the need to project that fear onto something. Some people stopped flying in airplanes, worried about a repeat attack—and for years afterward, air travel always dipped on the anniversary of 9/11.4 Of course, this was and is an irrational fear; it is safer to travel by plane than by car. According to the National Safety Council, in 2010 there were over 22,000 passenger deaths involving automobiles, while no one died in scheduled airline travel that year.5 Nevertheless, Congress responded by rushing through the USA PATRIOT Act six weeks after 9/11—a 240-plus page bill that was previously written, not available to the public prior to the vote, and barely available to the elected officials in Congress, none of whom read it through before casting their votes.6 Two weeks previous to the bill’s passage, President Bush had announced the establishment of the Office of Homeland Security to “develop and coordinate the implementation of a comprehensive national strategy to secure the United States from terrorist threats or attacks.” He explained that “[t]he Office will coordinate the executive branch’s efforts to detect, prepare for, prevent, protect against, respond to, and recover from terrorist attacks within the United States.”7 The office’s efforts culminated in the creation of the Department of Homeland Security (DHS) one year later as a result of the Homeland Security Act of 2002. This law consolidated executive branch organizations related to “homeland security” into a single Cabinet department; twenty-two total agencies became part of this new apparatus. The government, responding to the outcry from a fearful citizenry, was eager to “do something.” All of this (and much, much more), affecting all Americans, because of a localized event materially affecting only a few. But while the event directly impacted only a small percentage of the population, its impact was felt throughout the entire country.

But data gathered by The Post shows that U-Va. campus police officers made the most arrests against students involving the purchase or consumption of alcohol last year, and 46 of the department's 89 total arrests concerned charges of public swearing or intoxication. In comparison, ABC special agents arrested seven people between the ages of 18 and 22 in 2014, two of whom were Hispanic, and the rest were white. Of the seven arrested, only three were charged with buying or drinking alcohol underage, all of whom were white. The other four were restaurant and convenience store clerks arrested for allegedly selling alcohol to underage patrons. During the same period, Charlottesville city police officers made 35 arrests against U-Va. students in connection with alcohol-related violations, while Albemarle County officers made seven arrests, five of which occurred at the spring Foxfield steeplechase races. The Post obtained arrest statistics from three local departments that patrol in Charlottesville: the city police, the Albemarle County police and the university's campus police. All three departments retain records noting how many U-Va. students are arrested annually. The departments did not provide demographic data related to the arrests. The ABC does not keep records about arrests of U-Va. students, said spokeswoman Becky Gettings, but does retain information related to offenders' ages. The data shows that Charlottesville and Albemarle

In Depth Types of Effect Size Indicators Researchers use several different statistics to indicate effect size depending on the nature of their data. Roughly speaking, these effect size statistics fall into three broad categories. Some effect size indices, sometimes called dbased effect sizes, are based on the size of the difference between the means of two groups, such as the difference between the average scores of men and women on some measure or the differences in the average scores that participants obtained in two experimental conditions. The larger the difference between the means, relative to the total variability of the data, the stronger the effect and the larger the effect size statistic. The r-based effect size indices are based on the size of the correlation between two variables. The larger the correlation, the more strongly two variables are related and the more of the total variance in one variable is systematic variance related to the other variable. A third category of effect sizes index involves the odds-ratio, which tells us the ratio of the odds of an event occurring in one group to the odds of the event occurring in another group. If the event is equally likely in both groups, the odds ratio is 1.0. An odds ratio greater than 1.0 shows that the odds of the event is greater in one group than in another, and the larger the odds ratio, the stronger the effect. The odds ratio is used when the variable being measured has only two levels. For example, imagine doing research in which first-year students in college are either assigned to attend a special course on how to study or not assigned to attend the study skills course, and we wish to know whether the course reduces the likelihood that students will drop out of college. We could use the odds ratio to see how much of an effect the course had on the odds of students dropping out. You do not need to understand the statistical differences among these effect size indices, but you will find it useful in reading journal articles to know what some of the most commonly used effect sizes are called. These are all ways of expressing how strongly variables are related to one another—that is, the effect size. Symbol Name d Cohen’s d g Hedge’s g h 2 eta squared v 2 omega squared r or r 2 correlation effect size OR odds ratio The strength of the relationships between variables varies a great deal across studies. In some studies, as little as 1% of the total variance may be systematic variance, whereas in other contexts, the proportion of the total variance that is systematic variance may be quite large,

The book is limited in time and space to addressing population policies in the Young Turk era (1913–50) in Eastern Turkey. It begins with the Young Turk seizure of power in the 1913 coup d’état and ends with the end of Young Turk rule in 1950.1 It will describe how Eastern Turkey as an ethnically heterogeneous imperial shatter zone was subjected to various forms of nationalist population policies aimed at transforming the region into an ethnically homogeneous space to be included into the Turkish nation state. How was Eastern Turkey moulded by Young Turk population policies? Why was the Turkish process of nation formation so violent in this region? Why do political elites launch policies to increase homogeneity in their societies? These will be the guiding questions in this book. The focus will be on an account of the implementation of these nationalist population policies in the eastern provinces, in order to discuss the policies in detail. This book argues that the Young Turk nationalist elite launched this process of societal transformation in order to establish and sustain a Turkish nation state. In this process, ethnically heterogeneous borderland regions were subjected to more encompassing and more violent forms of population policies than the core regions. The eastern provinces were one of these special regions. This book highlights the role played by the Young Turks in the identification of the population of the eastern provinces as an object of knowledge, management, and radical change. It details the emergence of a wide range of new technologies of population policies, including physical destruction, deportation, forced assimilation, and memory politics, which converged in an attempt to increase population homogeneity within the nation state. The common denominator to which these phenomena can be reduced is the main theme of population policies. The dominant paradigms in the historiography of the great dynastic land empires can be characterized as a nationalist paradigm and a statist paradigm. According to the first paradigm, the phenomenon of nationalism led to the dissolution of the empires. Centrifugal nationalism nibbled at the imperial system for several decades until the empire crumbled into nation states. Due to their relatively early acquaintance with nationalism, the main force behind this nationalist disintegration was often located among minority groups such as Czechs, Serbs, Greeks, and Armenians. In this interpretation, the Young Turks too, were a nationalist movement that reacted to minority nationalisms by pushing for the establishment of a Turkish state in the Ottoman Anatolian heartland. In 1923, they succeeded when a unitary Turkish nation state rose from the ashes of the Ottoman Empire.

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understanding of this formula, it is useful to relate it to the discussion of hypothesis testing in Chapter 10. First, note that the difference of means, appears in the numerator: the larger the difference of means, the larger the t-test test statistic, and the more likely we might reject the null hypothesis. Second, sp is the pooled variance of the two groups, that is, the weighted average of the variances of each group.3 Increases in the standard deviation decrease the test statistic. Thus, it is easier to reject the null hypotheses when two populations are clustered narrowly around their means than when they are spread widely around them. Finally, more observations (that is, increased information or larger n1 and n2) increase the size of the test statistic, making it easier to reject the null hypothesis. Figure 12.1 The T-Test: Mean Incomes by Gender

The null hypothesis of normality is that the variable is normally distributed: thus, we do not want to reject the null hypothesis. A problem with statistical tests of normality is that they are very sensitive to small samples and minor deviations from normality. The extreme sensitivity of these tests implies the following: whereas failure to reject the null hypo thesis indicates normal distribution of a variable, rejecting the null hypothesis does not indicate that the variable is not normally distributed. It is acceptable to consider variables as being normally distributed when they visually appear to be so, even when the null hypothesis of normality is rejected by normality tests. Of course, variables are preferred that are supported by both visual inspection and normality tests. In Greater Depth … Box 12.1 Why Normality? The reasons for the normality assumption are twofold: First, the features of the normal distribution are well-established and are used in many parametric tests for making inferences and hypothesis testing. Second, probability theory suggests that random samples will often be normally distributed, and that the means of these samples can be used as estimates of population means. The latter reason is informed by the central limit theorem, which states that an infinite number of relatively large samples will be normally distributed, regardless of the distribution of the population. An infinite number of samples is also called a sampling distribution. The central limit theorem is usually illustrated as follows. Assume that we know the population distribution, which has only six data elements with the following values: 1, 2, 3, 4, 5, or 6. Next, we write each of these six numbers on a separate sheet of paper, and draw repeated samples of three numbers each (that is, n = 3). We

T-TESTS FOR INDEPENDENT SAMPLES T-tests are used to test whether the means of a continuous variable differ across two different groups. For example, do men and women differ in their levels of income, when measured as a continuous variable? Does crime vary between two parts of town? Do rich people live longer than poor people? Do high-performing students commit fewer acts of violence than do low-performing students? The t-test approach is shown graphically in Figure 12.1, which illustrates the incomes of men and women as boxplots (the lines in the middle of the boxes indicate the means rather than the medians).2 When the two groups are independent samples, the t-test is called the independent-samples t-test. Sometimes the continuous variable is called a “test variable” and the dichotomous variable is called a “grouping variable.” The t-test tests whether the difference of the means is significantly different from zero, that is, whether men and women have different incomes. The following hypotheses are posited: Key Point The independent-samples t-test is used when one variable is dichotomous and the other is continuous. H0: Men and women do not have different mean incomes (in the population). HA: Men and women do have different mean incomes (in the population). Alternatively, using the Greek letter m to refer to differences in the population, H0: μm = μf, and HA: μm ≠ μf. The formula for calculating the t-test test statistic (a tongue twister?) is As always, the computer calculates the test statistic and reports at what level it is significant. Such calculations are seldom done by hand. To further conceptual understanding of this formula, it is useful to relate it to the discussion of hypothesis testing in Chapter 10. First, note that the difference of means, appears in the numerator: the larger the difference of means, the larger the t-test test statistic, and the more likely we might reject the null hypothesis. Second, sp is the pooled variance of the two groups, that is, the weighted average of the variances of each group.3 Increases in the standard deviation decrease the test statistic. Thus, it is easier to reject the null hypotheses when two populations are clustered narrowly around their means than when they are spread widely around them. Finally, more observations (that is, increased information or larger n1 and n2) increase the size of the test statistic, making it easier to reject the null hypothesis. Figure 12.1 The T-Test: Mean Incomes by Gender

usually does not present much of a problem. Some analysts use t-tests with ordinal rather than continuous data for the testing variable. This approach is theoretically controversial because the distances among ordinal categories are undefined. This situation is avoided easily by using nonparametric alternatives (discussed later in this chapter). Also, when the grouping variable is not dichotomous, analysts need to make it so in order to perform a t-test. Many statistical software packages allow dichotomous variables to be created from other types of variables, such as by grouping or recoding ordinal or continuous variables. The second assumption is that the variances of the two distributions are equal. This is called homogeneity of variances. The use of pooled variances in the earlier formula is justified only when the variances of the two groups are equal. When variances are unequal (called heterogeneity of variances), revised formulas are used to calculate t-test test statistics and degrees of freedom.7 The difference between homogeneity and heterogeneity is shown graphically in Figure 12.2. Although we needn’t be concerned with the precise differences in these calculation methods, all t-tests first test whether variances are equal in order to know which t-test test statistic is to be used for subsequent hypothesis testing. Thus, every t-test involves a (somewhat tricky) two-step procedure. A common test for the equality of variances is the Levene’s test. The null hypothesis of this test is that variances are equal. Many statistical software programs provide the Levene’s test along with the t-test, so that users know which t-test to use—the t-test for equal variances or that for unequal variances. The Levene’s test is performed first, so that the correct t-test can be chosen. Figure 12.2 Equal and Unequal Variances The term robust is used, generally, to describe the extent to which test conclusions are unaffected by departures from test assumptions. T-tests are relatively robust for (hence, unaffected by) departures from assumptions of homogeneity and normality (see below) when groups are of approximately equal size. When groups are of about equal size, test conclusions about any difference between their means will be unaffected by heterogeneity. The third assumption is that observations are independent. (Quasi-) experimental research designs violate this assumption, as discussed in Chapter 11. The formula for the t-test test statistic, then, is modified to test whether the difference between before and after measurements is zero. This is called a paired t-test, which is discussed later in this chapter. The fourth assumption is that the distributions are normally distributed. Although normality is an important test assumption, a key reason for the popularity of the t-test is that t-test conclusions often are robust against considerable violations of normality assumptions that are not caused by highly skewed distributions. We provide some detail about tests for normality and how to address departures thereof. Remember, when nonnormality cannot be resolved adequately, analysts consider nonparametric alternatives to the t-test, discussed at the end of this chapter. Box 12.1 provides a bit more discussion about the reason for this assumption. A combination of visual inspection and statistical tests is always used to determine the normality of variables. Two tests of normality are the Kolmogorov-Smirnov test (also known as the K-S test) for samples with more than 50 observations and the Shapiro-Wilk test for samples with up to 50 observations. The null hypothesis of

Despite the continual calls for expanded background checks after mass public shootings, there is no evidence that background checks on private transfers of guns would have prevented any of the attacks. Nor is there any statistical evidence that indicates that these mass public shootings are rarer in states with background checks on private transfers. What we do find is that fatalities and injuries from mass public shootings increased in states after they imposed background checks on private transfers. States with background checks on private transfers tended to have relatively low rates of murders and injuries from mass public shootings before the passage of background checks on private transfers, and these rates became relatively high afterwards. Clearly, there is no evidence that these laws lower mass public shootings. There are real costs of expanding background checks to private transfers. In particular, the fees on private transfers reduce gun ownership, particularly among law-abiding poor blacks who live in high crime urban areas and who benefit the most from protecting themselves; they will be the ones most likely priced out of owning guns for protection. Without some benefits in terms of either reduced crime or mass public shootings, it is hard to see how these rules pass any type of cost-benefit test.

even in recent times, the empirical evidence does not support the claim that trade liberalization or incentive neutrality leads to faster growth. It is true that higher manufacturing growth rates have been typically associated with higher export growth rates (mostly in countries where export and import shares to GDP grew), but there is no statistical relation between either of these growth rates or degree of trade restrictions. Rather, almost all of successful export-oriented growth has come with selective trade and industrialization policies. In this regard, stable exchange rates and national price levels seem to be considerably more important than import policy in producing successful export-oriented growth

While it might have surprised onlookers, undergraduates in the 2000s were in fact having less sex than their predecessors in the 1980s and '90s - if you accepted their definition of sex as vaginal intercourse. (Those of us who grew up during the Clinton years learned from our president that activities other than intercourse do not constitute "sexual relations," however intimate they may be.)

This curve, which looks like an elongated S, is variously known as the logistic, sigmoid, or S curve. Peruse it closely, because it’s the most important curve in the world. At first the output increases slowly with the input, so slowly it seems constant. Then it starts to change faster, then very fast, then slower and slower until it becomes almost constant again. The transfer curve of a transistor, which relates its input and output voltages, is also an S curve. So both computers and the brain are filled with S curves. But it doesn’t end there. The S curve is the shape of phase transitions of all kinds: the probability of an electron flipping its spin as a function of the applied field, the magnetization of iron, the writing of a bit of memory to a hard disk, an ion channel opening in a cell, ice melting, water evaporating, the inflationary expansion of the early universe, punctuated equilibria in evolution, paradigm shifts in science, the spread of new technologies, white flight from multiethnic neighborhoods, rumors, epidemics, revolutions, the fall of empires, and much more. The Tipping Point could equally well (if less appealingly) be entitled The S Curve. An earthquake is a phase transition in the relative position of two adjacent tectonic plates. A bump in the night is just the sound of the microscopic tectonic plates in your house’s walls shifting, so don’t be scared. Joseph Schumpeter said that the economy evolves by cracks and leaps: S curves are the shape of creative destruction. The effect of financial gains and losses on your happiness follows an S curve, so don’t sweat the big stuff. The probability that a random logical formula is satisfiable—the quintessential NP-complete problem—undergoes a phase transition from almost 1 to almost 0 as the formula’s length increases. Statistical physicists spend their lives studying phase transitions.

In fact these statistics record an astonishingly low rate of gun-related violence in the late nineteenth century. The Home Office reported the results of three separate inquiries: hospital figures throughout England for fatal and nonfatal wounds arising from handguns in 189o-92; coroners' inquests on such accidents; and the number of burglars found carrying firearms over five years ending with December 31, 1892.121 In the course of three years, according to hospital reports, there were only 59 fatalities from handguns in a population of nearly 30 million people. Of these, 19 were accidents, 35 were suicides, and only 3 were homicides-an average of one a year. The report noted that in the 189o pistol homicide both the murderer and the victim had been foreigners.122 The number of injuries treated in hospitals for revolver or pistol wounds over the three years was 226.123 The coroners' inquests relative to the use of both pistols and other firearms for the same three years was 536, of which 443 were suicides, 49 were accidents, 32 were homicidal, and 12 not known. As for armed burglaries, no policeman had been shot dead, although several had been wounded by gunfire. Over the five-year period only 31 burglars had been found carrying arms, and only 18 had escaped by the use of guns.124 On the basis of these modest figures the bill was objected to as "absolutely unnecessary ... and that it attacked the natural right of everybody who desired to arm himself for his own protection and not to harm anybody else." Hopwood suggested that the government legislate with regard to knives and daggers, since the number of murders and suicides committed by them was "infinitely greater ... than those committed by means of revolvers." As with the 1870 licence statute, this bill was attacked as class legislation. Mr. Conybeare thought it would be better to drop it "so that the efforts of the Government might be devoted to some more worthy measure."121 The debate was adjourned until the next day, but in light of its reception it was prudently withdrawn. Behind the scenes, however, a House of Lords standing committee was at work during 1894 to produce a more acceptable bill.

There are also books that contain collections of papers or chapters on particular aspects of knowledge discovery—for example, Relational Data Mining edited by Dzeroski and Lavrac [De01]; Mining Graph Data edited by Cook and Holder [CH07]; Data Streams: Models and Algorithms edited by Aggarwal [Agg06]; Next Generation of Data Mining edited by Kargupta, Han, Yu, et al. [KHY+08]; Multimedia Data Mining: A Systematic Introduction to Concepts and Theory edited by Z. Zhang and R. Zhang [ZZ09]; Geographic Data Mining and Knowledge Discovery edited by Miller and Han [MH09]; and Link Mining: Models, Algorithms and Applications edited by Yu, Han, and Faloutsos [YHF10]. There are many tutorial notes on data mining in major databases, data mining, machine learning, statistics, and Web technology conferences.

Migration statistics offer a hint of the shift. More than 170,000 migrants and refugees arrived in Italy by sea last year; Syrians and Eritreans were the two largest groups among them, accounting for more than 76,000 people, according to Italy’s Interior Ministry. Gambians ranked a distant fifth. Yet during the first quarter of 2015, a relatively slow period with just 10,165 arrivals — Gambia was the leading country of origin, accounting for 1,413 of the migrants. The authorities have not published figures for April yet, but humanitarian and migration groups confirm that a majority of the arriving migrants came originally from sub-Saharan African countries — some directly, with Italy as a destination, but many end up here less deliberately.

Notice that the p value works by assuming there is no difference between your experimental groups. This is a counterintuitive feature of significance testing: if you want to prove that your drug works, you do so by showing the data is inconsistent with the drug not working. Because of this, p values can be extended to any situation where you can mathematically express a hypothesis you want to knock down. But p values have their limitations. Remember, p is a measure of surprise, with a smaller value suggesting that you should be more surprised. It’s not a measure of the size of the effect. You can get a tiny p value by measuring a huge effect — “This medicine makes people live four times longer” — or by measuring a tiny effect with great certainty. And because any medication or intervention usually has some real effect, you can always get a statistically significant result by collecting so much data that you detect extremely tiny but relatively unimportant differences. As Bruce Thompson wrote, Statistical significance testing can involve a tautological logic in which tired researchers, having collected data on hundreds of subjects, then conduct a statistical test to evaluate whether there were a lot of subjects, which the researchers already know, because they collected the data and know they are tired. This tautology has created considerable damage as regards the cumulation of knowledge.1

More generally, the lack of feedback applies to all higher-level use of force situations for officers. While officers are trained in how to properly utilize force, the need for more serious levels of force is rare. For example, the Bureau of Justice Statistics conducted the 2008 Police-Public Contact Survey as a supplement to the National Crime Victimization Survey. An estimated 1.4% of those surveyed had force used or threatened during their most recent contact with law enforcement (BJS, 2008). In a related study, Hickman, Piquero, and Garner (2008) found that 1.5% of police-citizen contacts resulted in either the use of force or the threat of force. Of these cases, only a very small percentage (0.2%) of police-citizen encounters resulted in lethal force (i.e., use of a firearm) being applied or threatened. Geller and Scott (1992) determined that the average officer would have to work 1,299 years in Milwaukee, 694 years in New York City, or 198 years in Dallas to be statistically expected to shoot and kill a suspect.

Unfortunately for the Inuit (and their Paleo imitators), the rest of the story isn’t so rosy. Turns out the Inuit are not healthy at all. They suffer from many chronic diseases and live, on average, ten years less than statistically matched Canadians (Choinière 1992; Iburg, Brønnum-Hansen, et al. 2001). In fact, they have the worst longevity of all populations in North America. There are many reasons for their short life expectancy: high rate of infections and TB, as well as a high suicide rate. While these may not be diet related (although more and more evidence suggests a strong connection between diet and the ability to fight of infection, and between diet and mood), Inuit also die of cancers of the GI tract and stroke, afflictions strongly correlated to diet (Paltoo and Chu 2004). Autopsy studies show they have less heart disease, likely due to their high omega-3 and low omega-6 and low-saturated-fat diet, but they are by no means free of heart disease (McLaughlin, Middaugh, et al. 2005). And there’s a possibility that autopsy statistics showing low heart disease are unreliable, based on really poor data collection (Bjerregaard, Young, et al. 2003; Bell, Mayer-Davis, et al. 1997). In fact, one of the likely reasons for their apparent low rates of heart disease and some cancers is their short life expectancy: Inuit eating their traditional diet simply don’t live long enough to demonstrate heart disease and cancer. In fact, the Westernization of their diet—adding the very foods the Paleo movement vilifies—may actually be prolonging their lives. A recent review of the literature suggests that a diet high in seafood does not lead to less heart disease and may lead to worse health (Fodor, Helis, et al. 2014)!

People were killed, most of them Palestinians, including unarmed innocents. People are supposed to read this and say, "Wow, a supporter of Israel is saying that?! He must be honest! According to the United Nations, 96.5% of the deaths in this summer's Gaza War (including Israeli soldiers) were those of Palestinians (2,104 out of 2,179). "Most" means "majority." "Majority" means "more than half the total." 96.5% is not "most." 96.5% is "almost all." Sure, in this statement, "most" might be technically accurate, but it's not precise, sincere, or complete. When you hear "most," you don't think, "Oh, he must mean 96.5%." Also, 70% of the Palestinian deaths were those of unarmed innocents, including 495 children. "Many" means "numerous." "Many doesn't necessarily suggest any sort of relative proportion to the total. 70% is not "many." Actually, 70% is "most." Sure, "many" might be technically accurate, but, again, it's not precise, sincere, or complete. When you hear "many," you don't think, "Oh, he must mean 70%." Friedman does not use any statistics in his assessment. And why would he? It would have sounded quite different if he had written, "People were killed, almost all of them Palestinians, most of them unarmed innocents." But Friendman, who is attempting to make a point about journalistic integrity, is not interested in being specific here. He is practicing "truthful deception.

In the United Kingdom, transport is mostly provided to the public via road, air, and water. The county has a vast road network with 29,145 miles of main roads. However, road transport has experienced significant growth since 1952 with the increasing number of vehicles and cars in the country. Railways have also grown relatively slowly; but the statistics show that in 1952, taxi cabs or cars almost covered 27% of total transportation.

In 1976, U.S. relations with Nigeria reached an all-time low... Henry Kissinger, whose indifference to Africa bordered on cynicism, decided at last to meet Joseph Garba, the Nigerian foreign minister, at the United Nations. In a gambit of condescending pleasantness, Kissinger asked Garba what he thought America was doing wrong in Africa. To which Garba replied stonily: “Everything!” Kissinger’s next comment was both precious and, I regret to admit, true. He said: “Statistically that is impossible. Even if it is unintentional, we must be doing something right.