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Category: Statistics

The general theory, methods, and philosophy of the Science of Guessing What Is.

June 25, 2018 | 5 Comments

Global Warming: Thirty Years Of Hype, Hysteria & Hullabaloo

In the late spring of 1988, Senator Tim Wirth from Colorado (guess his party) called the Weather Bureau and asked what historically was the hottest day of the year in Washington, DC.

He needed heat for the theater he was cooking up.

He got it. That June, he recalled, was “stiflingly hot.” To give nature a boost, on the night of 22 June, he snuck into the Senate hearing room and opened all the windows. The air conditioning was either switched off or chose that moment to break.

Wirth later boasted to PBS that

when the hearing occurred there was not only bliss, which is television cameras in double figures, but it was really hot…

So [NASA’s James] Hansen’s giving this testimony, you’ve got these television cameras back there heating up the room, and the air conditioning in the room didn’t appear to work. So it was sort of a perfect collection of events that happened that day, with the wonderful Jim Hansen, who was wiping his brow at the witness table and giving this remarkable testimony.

In that manufactured swelter on 23 June 1988, Global Warming was born. Happy Anniversary.

Today, thirty years later, Global Warming is dead. Make that undead. Its corpse still walks among us, awaiting its final stake through its heart.

Winter is Coming

Politicians like Wirth, and the scientists in their employ, had a streak of good luck. Hansen said it would get hotter, and then it did. People doing things like breathing and driving cars were adding “greenhouse gases” to the atmosphere at rates faster than ever before. The correlation between increasing heat and gas was obvious, and it quickly became a cause. Both in the physical and social sense.

There was some reason to believe Hansen was right in those early days. It is a trivial truth that man influences the climate. And scientists had already accepted the idea that man could significantly affect it. A decade before Hansen’s performance, the consensus was that man was driving temperatures dangerously down. Pollution from cars and the like was knocking back the sun’s rays, which was going to cause global cooling.

Global cooling was no small thing. In April 1975 Newsweek spoke fear in “Our Cooling World“. Global cooling was going to cause “serious political implications for just about every nation on earth,” “The drop in food production could begin quite soon,” “devastating outbreak of tornadoes”, “national boundaries make it impossible for starving peoples to migrate from their devastated fields,” and so forth.

Sound familiar?

When All Agreed

The global cooling consensus of the 1970s was small, but not insignificant because climatology was only then developing into a separate field from meteorology and other atmospheric sciences, and all these sciences were small.

That man was having a devastating, irreversible-without-government-action cooling effect on the earth’s climate would later become something of an embarrassment to climatologists. Which is why they did their best push global cooling into the memory hole. But there was so much material, it overflowed. Even Spock warned of the coming snow (don’t miss the earnest interview with Stephen Schneider, who would go on to give many earnest interviews about global warming).

But by the time Wirth staged his event, 1978 was ancient history. We knew lots more about the atmosphere in 1988 and had exponentially better computers. Besides, just look at those thermometers inching up! And did you see that scary hockey stick? We must Save The Planet!

Celebrities Are Our Leaders

It wasn’t long before a politician made an Oscar-winning documentary film about global warming. That the film was saturated with errors and made laughable predictions did not matter. Global warming had to be as frightening as the film portrayed, otherwise the politician-turned-actor hosting it would not have looked so serious.

It wasn’t just politicians. Important people the world over were warming to the coming heat. Actors, musicians, pastors, people famous for being famous, chefs, novelists, school teachers, bureaucrats, activists, academics in such widely varying fields as sociology to psychology, and of course lawyers and news readers. Oh, plus a handful of physical scientists (most kept their heads down).

When celebrities speak, we listen. Even if they’re wrong in the details, that so many elites knew global warming was on its way was sufficient and convincing evidence something had to be done.

Nine Most Terrifying Words

That something was government. More and larger government. The government took up this challenge and did what it did best: it spent money. Lots of it. Soon, every major grant-reliant scientific association, no matter how tenuous its connection to atmospheric physics, issued official statements on how horrible global warming was going to be—once it got here.

Researchers realized you were only half way through this article and that you have to click here to read the rest!

June 22, 2018 | 5 Comments

Peter Singer Wants to Teach the World His Song Of Death

It’s always amazing to me when I see Peter Singer’s name crop up on an article. I keep guessing he’d have been tarred and feathered and purged from polite society by now.

But no. He’s tolerated, because tolerating lunatic despicable blood-and-death-loving savages like Singer is what we do. We on the right are nice people. We are nice to Singer.

Singer is not nice to us. He joins two others, who I bet have never ever said “I wish my mother aborted me”, in writing yet another article claiming there are too many people. I also bet Singer and his co-authors feel they are not part of the surplus population.

Cracked Crystal Balls

They begin with Paul “Population Bomb” Ehrlich, whose overpopulation predictions were so monumentally wrong that even climatologists blush when reading them.

But rrror, even gross malfeasant preposterous error, is no bar from being venerated as a prophet when your heart is in the right place. And Ehrlich’s heart is just as black as Singer’s.

Ehrlich, a biologist, argued that if voluntary family planning didn’t reduce population sufficiently to avoid famine and other natural disasters, then coercion and the withdrawal of food aid to some countries would be necessary and justifiable.

Wait. Did he say remove food to avoid famine? I don’t get it, but then I am not a tenured biologist.

Anyway, starvation is a scientifically proven way to kill off undesirables. Just ask the Ukrainians who lived through an application of Ehrlich’s far-left policy. No one but God knows the total, but guesses say from three to eight million were Ehrliched in the Holodomor.

That sounds like a lot, but it’s not even one percent of the world’s population. We’re going to have to do better.

First Person to Say ‘Feminist’ Loses

Feminists, Singer and pals tell us, were the first to object to China’s original one-child policy. But feminists have now seen the dark.

Both feminists and population stabilization advocates now agree that providing reproductive health services to women is first and foremost a right in itself, as well as the best and most ethical way to slow population growth.

Reproductive health services is the super fun euphemism invented by the left which means cutting enwombed babies into small parts and selling them to raise shopping money. Incidentally, if feminists have the “right” to kill, why don’t we have the “right” to, as writer Kevin Williamson may or may not have meant seriously, string abortionists up by the neck until dead? Just asking.

Diaper Sales

The trio of population stabilization advocates tell us that…you ought to click here to read the rest.

June 21, 2018 | 1 Comment

Chapter 1 Excerpt from Uncertainty: The Soul of Probability, Modeling & Statistics

Buy the book!

Necessary & Conditional Truth

Given “x,y,z are natural numbers and x>y and y>z” the proposition “x>z” is true (I am assuming logical knowledge here, which I don’t discuss until Chapter 2). But it would be false in general to claim, “It is true that ‘x>z‘.” After all, it might be that “x = 17 and z = 32“; if so, “x>z” is false. Or it might be that “x = 17 and z = 17“, then again “x>z” is false. Or maybe “x = a boatload and z = a humongous amount”, then “x>z” is undefined or unknown unless there is tacit and complete knowledge of precisely how much is a boatload and how much is a humongous amount (which is doubtful). We cannot dismiss this last example, because a great portion of human discussions of uncertainty are pitched in this way.

Included in the premise “x,y,z are natural numbers and x>y and y>z” are not just the raw information of the proposition about numbers, but the tacit knowledge we have of the symbol >, of what “natural numbers” are, and even what “and” and “are” mean. This is so for any argument which we wish to make. Language, in whatever form, must be used. There must therefore be an understanding of and about definitions, language and grammar, in any argument if any progress is to be made. These understandings may be more or less obvious depending on the argument. It is well to point out that many fallacies (and the best jokes) are founded on equivocation, which is the intentional or not misunderstanding double- or multiple-meanings of words or phrases. This must be kept in mind because we often talk about how the mathematical symbols of our formulae translate to real objects, how they matter to real-life decisions. A caution not heard frequently enough: just because a statement is mathematically true does not mean that the statement has any bearing on reality. Later we talk about how the deadly sin of reification occurs when this warning is ignored.

We have an idea what it means to say of a proposition that it is true or false. This needs to be firmed up considerably. Take the proposition “a proposition cannot be both true and false simultaneously”. This proposition, as I said above, is true. That means, to our state of mind, there exists evidence which allows us to conclude this proposition is true. This evidence is in the form of thought, which is to say, other propositions, all of which include our understanding of the words and English grammar, and of phrases like “we cannot believe its contrary.” There are also present tacit (not formal) rules of logic about how we must treat and manipulate propositions. Each of these conditioning propositions or premises can in turn be true or false (i.e. known to be true or false) conditional on still other propositions, or on inductions drawn upon sense impressions and intellections. That is, we eventually must reach a point at which a proposition in front of us just is true. There is no other evidence for this kind of truth other than intellection. Observations and sense impressions will give partial support to most propositions, but they are never enough by themselves except for the direct impressions. I explore this later in the Chapter on Induction.

In mathematics, logic, and philosophy popular kinds of propositions which are known to be true because induction tells us so are called axioms. Axioms are indubitable—when considered. Arguments for an axiom’s truth are made like this: given these specific instances, thus this general principle or axiom. I do not claim, and it is not true, that everybody knows every axiom. The arguments for axioms must first be considered before they are believed. A good example is the principal of non-contradiction, a proposition which we cannot know is false (though, given we are human, we can always claim it is false). As said, for every argument we need an understanding of its words and grammar, and, for non-contradiction specifically, maybe the plain observation of a necessarily finite number of instance of propositions that are only true or only false, observations which are consonant with the axiom, but which are none of them the full proof of the proposition: there comes a point at which we just believe and, indeed, cannot do other than know the truth. Another example is one of Peano’s axioms. For every natural number, if x = y then y = x. We check this through specific examples, and then move via induction to the knowledge that it is true for every number, even those we have not and, given our finiteness, cannot consider. Axioms are known to be true based on the evidence and faith that our intellects are correctly guiding us.

This leads to the concept of the truly true, really true, just-plain true, universally, absolutely, or the necessarily true. These are propositions, like those in mathematics, that are known to be true given a valid and sound chain of argument which leads back to indubitable axioms. It is not possible to doubt axioms or necessary truths, unless there be a misunderstanding of the words or terms or chain of proof or argument involved (and this is, of course, possible, as any teacher will affirm). Necessary truths are true even if you don’t want them to be, even if they provoke discomfort, which (again of course) they sometimes do. Peter Kreeft said: “As Aristotle showed, [all] ‘backward doubt’ terminates in two places: psychologically indubitable immediate sense experience and logically indubitable first principles such as ‘X is not non-X’ in theoretical thinking and ‘Good is to be done and evil to be avoided’ in practical thinking”.

A man in the street might look at the scratchings of a mathematical truth and doubt the theorem, but this is only because he doesn’t comprehend what all those strange symbols mean. He may even say that he “knows” the theorem is false—think of the brave soul who claims to have squared the circle. It must be stressed that this man’s error arises from his not comprehending the whole of the argument. Which of the premises of the theorem he is rejecting, and this includes tacit premises of logic and other mathematical results, is not known to us (unless the man makes this clear). The point is that if it were made plain to him what every step in the argument was, he must consent. If he does not, he has not comprehended at least one thing or he has rejected at least one premise, or perhaps substituted his own unaware. This is no small point, and the failure to appreciate it has given rise to the mistaken subjective theory of probability. Understanding the whole of an argument is a requirement to our admitting a necessary truth (our understanding is obviously not required of the necessary truth itself!).

From this it follows that when a mathematician or physicist says something akin to, “We now know Flippenberger’s theorem is true”, his “we” does not, it most certainly does not, encompass all of humanity; it applies only to those who can and have followed the line of reason which appears in the proof. That another mathematician or physicist (or man in the street) who hears this statement, but whose specialty is not Flippenbergerology, conditional on trusting the first mathematician’s word, also believes Flippenberger’s theorem is true, is not making (to himself) the same argument as the theory’s proponent. He instead makes a conditional truth statement: to him, Flippenberger’s theorem is conditionally true, given the premise of accepting the word of the first mathematician or physicist. Of course, necessary truths are also conditional as I have just described, so the phrase “conditional truth” is imperfect, but I have not been able to discover one better to my satisfaction. Local or relative truth have their merits, but their use could encourage relativists to believe they have a point, which they do not.

Besides mathematical propositions, there are plenty other of necessary truths that we know. “I exist” is popular, and only claimed to be doubted by the insane or (paradoxically) by attention seekers. “God exists” is another: those who doubt it are like circle-squarers who have misunderstood or have not (yet) comprehended the arguments which lead to this proposition. “There are true propositions” always delights and which also has its doubters who claim it is true that it is false. In Chapter 2 we meet more.

There are an infinite number and an enormous variety of conditional truths that we do and can know. I don’t mean to say that there are not an infinite number of necessary truths, because I have no idea, though I believe it; I mean only that conditional truths form a vaster class of truths in everyday and scientific discourse. We met one conditional truth above in “x>z“. Another is, given “All Martians wear hats and George is a Martian” then it is conditionally true that “George wears a hat.” The difference in how we express this “truth is conditional” is plain enough in cases like hat-wearing Martians. Nobody would say, in a general setting, “It’s true that Martians wear hats.” Or if he did, nobody would believe him. This disbelief would be deduced conditional on the observationally true proposition, “There are no Martians”.

We sometimes hear people claim conditional truths are necessary truths, especially in moral or political contexts. A man might say, “College professors are intolerant of dissent” and believe he is stating a necessary truth. Yet this cannot be a necessary truth, because no sound valid chain of argument anchored to axioms can support it. But it may be an extrapolation from “All the many college professors I have observed have been intolerant of dissent”, in which case the proposition is still not a necessary truth, because (as we’ll see) observational statements like this are fallible. Hint: The man’s audience, if it be typical, might not believe the “All” in the argument means all, but only “many”. But that substitution does not make the proposition “Many college professors are intolerant of dissent” necessarily true, either.

Another interesting possibility is in the proposition “Some college professors are intolerant of dissent,” where some is defined as at least one and potentially all. Now if a man hears that and recalls, “I have met X, who is a college professor, and she was intolerant of dissent”, then conditional on that evidence the proposition of interest is conditionally true. Why isn’t it necessarily true? Understand first that the proposition is true for you, too, dear reader, if we take as evidence “I have met X, etc.” Just as “George wears a hat” was conditionally true on the other explicit evidence. It may be that you yourself have not met X, nor any other intolerant-of-dissent professor, but that means nothing for the epistemological status of these two propositions. But it now becomes obvious why the proposition of interest is not necessarily true: because the supporting evidence “I have met X, etc.” cannot be held up as necessarily true itself: there is no chain of sound argument leading to indubitable axioms which guarantees it is a logically necessity that college professors must be intolerant of dissent. (Even if it sometimes seems that way.)

We only have to be careful because when people speak or write of truths they are usually not careful to tell us whether they have in mind a necessary or only a conditional truth. Much grief is caused because of this.

One point which may not be obvious. A necessary truth is just true. It is not true because we have a proof of it’s truth. Any necessary truth is true because of something, but it makes no sense to ask why this is so for any necessary truth. Why is the principle of non-contradiction true? What is it that makes it true? Answer: we do not know. It is just is true. How do we know it is true? Via a proof, by strings of deductions from accepted premises and using induction, the same way we know if any proposition is true. We must ever keep separate the epistemological from the ontological. There is a constant danger of mistaking the two. Logic and probability are epistemological, and only sometimes speak or aim at the ontological. Probability is always a state of the mind and not a state of the universe.

June 15, 2018 | 12 Comments

Statistics Are Now Hate Facts

Hate facts are true statements about reality that our elites demand remain occult and unuttered.

Elites don’t yet say that members of the elite cannot know hate facts, but they being good gnostics do try to control the spread of hate facts among the indigenous populants of these once United States.

Examples? We had many here. See the old post “Black And White Homicide Rates: Who’s Killing Whom?” Using official statistics, numbers which are therefore beyond dispute (“That’s a joke, son”), it was demonstrated that blacks murder at much higher rates than whites, that more blacks (proportionally) kill whites than whites kill blacks, and so on.

Like all hate facts, people know the truth of these statements, but you can see from the tone of the comments that some thought it in poor taste to state in public what we all knew to be true.

The fear of hate fact haters (our elites) is that hate facts will be used to generate hate, which is to say, to infer undesirable or incorrect explanations for the hate facts. Now it has been observed that blacks kill at higher rates than whites, and have done so for many decades, but the numbers themselves do not say why the difference exists. Some will say that the difference is caused because blacks and whites are different. Which is a trivially true statement. If it wasn’t trivially true, we would never be able to tell the difference between the races. The numbers do not however say why blacks as blacks kill at higher rates than whites as whites.

What to do about the difference in murder rate (or about any hate fact) is an altogether separate question. The answer can never be found in the hate facts themselves. The numbers are barren of cause. Cause and action have to be discovered outside them. Hate fact haters say that when the wrong people learn of hate facts, the cause they ascribe will invariably be some -ism or -phobia and the action (if required) will usually or always be hate. These conclusions do not necessarily follow.

It will be true sometimes that incorrect causes and unpalatable actions are proposed. But it is also true that hate fact haters come to incorrect causes and suggest actions that do more harm than good. We all know this story well enough about crime and race not to repeat it here.

Finally we come to confirmation about hate facts in a story discovered by reader Vince Lee. “Scholars claim that statistics ‘serve white racial interests’“.

Three British professors recently claimed that statistical analyses have been weaponized to “serve white racial interests” within academia and beyond.

Led by David Gillborn, a professor at the University of Birmingham, the professors argue that math serves white interests because it can “frequently encode racist perspectives beneath the facade of supposed quantitative objectivity.”

“Numbers are social constructs and likely to embody the dominant (racist) assumptions that shape contemporary society.”

“Contrary to popular belief, and the assertions of many quantitative researchers, numbers are neither objective nor color-blind,” Gillborn and his team assert in their article for the journal Race, Ethnicity, and Education.

7! 14! 23.5!

There’s some n-words for you, baby. N-umbers. Weapons. I slipped ’em in and you didn’t even notice.

I won’t tell you how “7” encodes a racist perspective beneath the facade of supposed quantitative objectivity because I’m already risking the censor by printing it. Saying what it means can land me prison.

Enough dumb jokes. The truth is these professors are frightened of hate facts. They know what numbers mean, and they know you know what numbers mean when you see them, but they wrongly suspect you will always ascribe incorrect causes and that you will propose harmful actions when you learn of the numbers.

These men have formed the field of “QuantCrit’—a portmanteau for ‘quantitative analysis’ and ‘critical race theory'”. They say “quantitative data is often gathered and analyzed in ways that reflect the interests, assumptions, and perceptions of White elites”, which is nonsense because it is impossible for any number to contain its cause. An analysis can be wrong when it ascribes the wrong cause. But numbers can never be wrong, nor can an analysis, unless they are lied about (I’m excepting mistakes).

Whatever else this is, it is a play for power. “The professors also acknowledge the tension between social justice and quantitative analysis, saying that while statistics can be used to point out the failures of social justice programming, ‘data is often used to shut down, silence, and belittle equity work.'”

In other words, hate facts undercut and disprove the theses of equality and diversity and they aren’t happy of it. Solution? Ban hate facts (in effect) by calling the hate facts themselves racsit, sexist, etc. etc. etc.