William M. Briggs

Statistician to the Stars!

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Barcode People From Birth — Guest Post By Faith Reader

Despotism and tyranny wear many cloaks.  Modern Western leaders are above using raw, brute power to fulfill their desires.  Instead, they wheedle and whine and the public gives in, worn out and worse for the wear.  Thankfully, these days may soon be a thing of the past, if Elizabeth Moon gets her way.  The science fiction writer told the BBC last month:

“If I were empress of the Universe I would insist on every individual having a unique ID permanently attached – a barcode if you will; an implanted chip to provide an easy, fast inexpensive way to identify individuals.”

She goes on to say what a boon it would be wartime that soldier could differentiate between the opposing armies and the innocent civilians. It is a pity that she doesn’t think this through, and consider the advantage that bar-coded people would have for dictators with genocide on their mind.

Moon isn’t the first to come up with the idea of tagging the population, proving yet again that a bad idea never dies. She has tapped into something that appeals to the nanny-staters who positively drool at the prospect of having absolute power over every nook and cranny of everyone’s life. It is well known that most people are fools and will vote Republican, even if is against their interests. Therefore, they need to be lead around by the nose. “Everyone” doesn’t include those who hold the leash.

In the United States, many still cling to the idea that the people have supremacy over the government, and that the government is “of the people, by the people, and for the people.” In the last forty years (again, in the United States) there has been a reversal of who’s in charge, and the preponderance of evidence shows that the government rules the people, rather than the other way around.

It is neither the responsibility nor the obligation of the government supervise the non-criminal behavior of the people. If people pay their taxes and strive to obey laws, then the government ought to leave them alone so they can engage in their right to “life, liberty, and the pursuit of happiness.” Just because having people tagged makes life easier for the government not only to “identify” everyone, but also to find tax cheats and detect other criminal activity is not a reason to implement a massive bar-coding scheme.

Recent history suggests that some politicians may resist the idea of electronic tagging. In New York State there was a flap about fingerprinting food stamp applicants. The mayor of New York City was all for it, but the governor believed that practice treated welfare applicants as criminals. Using the governor’s logic, bar-coding the public would be akin to treating them as criminals.

Although, if the Affordable Care Act passes muster with the U.S. Supreme Court, there could be a basis to open the door for electronic health surveillance. Maybe the technology isn’t there yet, but such a smart chip could monitor not only one’s vitals, but also whether if one imbibed more than 16 ounces of soda, enjoyed more than the daily quota of adult beverages, or smoked a cigarette.

Our founders recognized that such a grievous state of government surveillance and interference was possible, and they had the foresight to propose a way out when they drafted the Declaration of Independence:

“But when a long train of abuses and usurpations, pursuing invariably the same Object evinces a design to reduce them under absolute Despotism, it is their right, it is their duty, to throw off such Government, and to provide new Guards for their future security.”

The Difference Between Technical And Plain English Correlation

Since the subject has come up so often, today a note on the words correlated and correlation. They have technical definitions and plain English meanings. The two definitions overlap but they are not equivalent.

Suppose you have these two propositions: X = “Jack has an IQ of 107” and Y = “Jack makes $72,000 a year.” And you wonder, does Jack’s IQ have a bearing on his salary? Or does Jack’s salary have a bearing on his IQ? Higher incomes might imply a softer lives, more leisure time and perhaps more bodily ease for the little gray cells to flourish. So the latter question might be answered “yes.”

Problem is, we can’t answer either of these two questions without making recourse to other evidence. And if we want to quantify the answers, we also have to fix our meaning of “has a bearing.” This part is simple. If we knew X or assumed X was true for the sake of argument, then given X the probability of Y being true changes if we knew or assumed X was false. This “has a bearing” captures what we mean when we say X causes Y or if X is merely related to Y but is perhaps not in the “causal path” of Y.

For instance, there might be some W that causes both X and Y simultaneously; in this case knowledge of X “has a bearing” on knowledge of Y. Or it might be that X caused A which causes B which causes C and so on right up to Y. Or this path might be reversed. But once again, knowledge of X has a bearing on our knowledge of Y, even if we know nothing directly of A, B, C, etc.

A classical statistician wondering whether Jack’s IQ has a bearing on his salary would probably venture forth and collect data on Jill’s IQ and salary, and likewise data from Bill and from Alice, and from Will and Wilma, and so on. This maneuver adds the additional information or evidence we required. Why do we require this? Well, what is the answer to this:

     Pr (Y | X) = ?

This is “What is the probability Y is true given (or assuming) X is true?” It has no answer in this form. If you find yourself supplying an answer, it is because you are implicitly adding extra evidence not stated in the formula. That is, you are doing something like this:

     Pr (Y | X & A) = some number between 0 and 1,

where A was mentally supplied by you. Just as it was supplied by the statistician who collected the other pairs of IQ and salaries, which also implies (this is part of the statistician’s “A”) that these pairs are relevant to Jack; it also assumes that the causal path (and our certainty in it) from X to Y is the same for all these pairs. (This sameness can be changed, as in regression say, but sameness is the first belief.)

Now imagine we make a plot of our pairs: at each observation “X = Jill has an IQ of 108” and Y = “Jill has a salary of $74,500” we make a dot at (108, 74500), and so forth. To the extent that a straight line draw through the midst of these scattered points approximates the points themselves, the higher we say the correlation is. If all the points lined up exactly on this straight line, the correlation is “1” or exact. If the points are spread from near to far and do not look at all friendly to the line, the correlation is “0” or nearly.

This is the technical definition: if our gathering of Xs and Ys can be approximated by a straight line, they are said to be “correlated” or that the two variables have “non-zero correlation.”

Now imagine a sine wave. Here we have statements like X1 = “We are at time point 1” or X2 = “We are at time point 1.01” or whatever, with Y = “The sine at time point 1 is 0.84” and Y = “The sine at time point 1.01 is 0.85” and so forth. In this case, given the additional information on the formula of the sine, we can say that X directly causes Y to take the values it does. That is (ignoring rounding error),

     Pr (“The sine at time point 1 is 0.84” | “We are at time point 1” & S) = 1,

where S is the knowledge we have of the sine (see any trig or intro calculus book for this). But if we plotted1 a bunch of these Xs and Ys we would find the (technical) correlation between these Xs and Ys was somewhere in the vicinity of 0. This strange happenstance is because the extra evidence here purposely ignores S, the knowledge of the sine wave. It replaces S with some M, which assumes that, given X, our knowledge of Y is quantified by a normal distribution. Why ignore S? Well, just so we can replace it with M. If this seems odd, then know that in many statistical models relevant information like S is often ignored.

Anyway, we finally arrive at the most succinct definitions. Technical correlation is when a straight line approximates pairs of Xs and Ys. Plain English correlation is when knowledge of X changes the certainty we have in Y. Plain English correlation thus encapsulates technical correlation. Plain English correlation can also be called relevance, which is similar (but not identical to) technical “dependence.” About that, another day.


1For once, Wikipedia has some good plots of functions like the sine where we know there is causality but where the correlation is 0 or near 0; they also have the formula for technical correlation.

Are There Any Arguments Against Eugenics Left?

Most, or even all, progressives say they are against eugenics. Yet most, or all, progressives were against the recent Prenatal Nondiscrimination Act which would have outlawed sex-selective abortions in these United States.

That Act failed in the House of Representatives with Ron Paul, six other Republicans, and all but twenty Democrats voting to abort it. Word was that progressives, women’s “rights” groups, and even a few Asian-American groups opposed the bill.

Now it is obvious that killing a female fetus because it is a female just is eugenics in practice. And so is killing a fetus that differs in any way from the ideal created in the mind of the non-mother-to-be. Killing a fetus which is guessed (genetic tests are not perfect; there is error) will be retarded or, say, medically “defective” is exactly what eugenics is. But killing a fetus because it would interfere with a woman’s plans for the weekend is not strictly eugenical, at least not in a strong sense of active deselection.

Incidentally, and entirely off topic, what do the selfish-genes folks say about the enormous and growing rate of self-gene deselection? (It’s at this point in the evolutionary psychology discussion that the subject is changed.)

It was, as even PBS reminds us, progressives a century ago who led groups like the Race Betterment Foundation. “In 1923, organizers founded the American Eugenics Society, and it quickly grew to 29 chapters around the country.” Woodrow Wilson was positively bullish on improving the human stock. And so forth. (See also this article by professor of anthropology Jonathan Marks.)

But after 1945 a great many who had been championing the culling of the less desirable sobered up or were shamed into silence. These feelings grew so that it was eventually reflexive for any right-thinking person to condemn eugenics.

Except in the case of abortions, where it is actively encouraged. This attitude can be summarized: Killing people once they are outside the womb is wrong, killing them before they emerge is not wrong. (Except that even this attitude is changing: see this.)

So let us ask progressives and leftists out there (1) why on moral grounds they are for allowing sex selective abortions, (2) why on moral grounds they are for allowing abortions for what they claim are “defective” or “less desirable” human beings, and (3) why on moral grounds they are simultaneously against eugenics. Keep in mind that it is everywhere females who are killed off in the wombs at much higher rates than males.

It is a fallacy to argue, incidentally, that if the Prenatal Nondiscrimination Act passed it would be difficult to enforce. That law and its policing is irrelevant to the questions just asked. It is a fallacy to argue, for example, that if the law passed “all women seeking an abortion are suspects” in a crime, as this person said, thus eugenics is morally right. It is also a fallacy to argue that the Act would have just plain outlawed abortion, for even if that turned out to be the case, it says nothing about whether abortion for sex selection or against “defectives” is morally right.

The questions of interest have nothing at all to do with what laws exist or what laws might exist. They are purely questions on the ethics of eugenics, whether or not eugenics is lawful. Consider the analogy that it is against the law to take certain drugs, yet many people can still argue that taking these drugs is not morally wrong. We can argue another day whether laws for or against eugenics are desirable, harmful, enforceable, whatever. Today they are of not the slightest interest (except as a means to inform us that some people are for sex-selective abortion, i.e. eugenics in practice).

And don’t forget it is not just sex-selection we are interested in, but the killing of any fetus seen as less than desirable for reasons other than convenience.

Remember that we are ladies and gentleman.

Gloom, Despair, Email Spoofing, And Kahan’s Science Literacy Paper

Somebody spoofed my Yahoo email address which I use for ordering, registrations and the like. Sent hundreds of emails to my contact list yesterday.

Now I ordinarily run Linux, which you will all agree is superior to all other operating systems. But for the past few days, because of work, I had to log on to a Windows machine. I checked my email on that machine. It was after this that I was spoofed, hacked, or scammed. Whatever you call it, it was a pain in the keister.

This happenstance in time is what we statisticians call a curious coincidence. It could be that Windows, notorious as it is for being leakier than a canoe made of screen doors, allowed some villain to sneak in and steal my password. Or it could be that some clever fellow guessed this password, which I humbly admit was magnificently complicated. Or it could be something else.

That’s probability for you: not enough information to say for certain. And I want to say for certain so I know to whom or to what to direct my cursing.

So I was already in a petulant mood when I got a tweet from Paul Matthews ‏(@etzpcm) asking me to look at the paper “The polarizing impact of science literacy and numeracy on perceived climate change risk” by somebody with the name of Danny Kahan, who looks to be a lawyer. At least he sits in a law department.

The paper is a poll, a survey of the kind telemarketers, politicians, and in increasing number, sociologists run. You know what I mean. A bunch of questions asked of hapless citizens, the results fed into a needlessly complicated statistical analysis which produces grand theorizing all “proved” with wee p-values. The kind of thing we review on this blog ad nauseam.

Science literacy. Just what is that? This question? “The government interferes far too much in our everyday lives.” Well, that’s one of their questions. I wonder how the responses would be if they asked this after hearing Nanny Bloomberg’s plan to steal the (liquid) candy from the hands of New York City’s babies.

Nah, by “literacy” (numerical) they mean the ability to answer gotcha questions like this:

In a lake, there is a patch of lilypads. Every day, the patch doubles in size. If it takes 48 days for the patch to cover the entire lake, how long would it take for the patch to cover half of the lake?

Sure it’s easy (for us superior beings). But admit it, Danny boy. How many of you and your authors got these zingers right without blinking or thinking? Tell the truth. Your mother might read this blog.

Funny thing. They asked only two questions about how the climate works. Imagine that. Science literacy about climate change fully discerned by asking “Does the Earth go around the Sun, or does the Sun go around the Earth?” and “How long does it take for the Earth to go around the Sun?” That’s the beauty of theory, friend, which Dan and company provide in great heaps. All kinds of verbiage about the “science comprehension thesis” versus the “cultural cognition thesis”. Golly.

Here’s the main finding:

As respondents’ science-literacy scores increased, concern with climate change decreased (r=−0.05, P=0.05). There was also a negative correlation between numeracy and climate change risk (r=−0.09, P<0.01).

Just look at those publishable p-values! But wait. What’s that? As people’s so-called “science-literacy” increases, their concern about climate change decreases?

Look. The “r” means linear correlation, and here is a number of a size that we scientists “trivial”, “vanishingly small”, or “Are you kidding?” The effect is nearly non-existent. Remember: this correlation is in this sample of survey respondents. Replication would almost certainly show that this effect vanishes like reason at the New York Times editorial office.

Ah geez. Just skip it. The whole study is based on a fallacy. A citizen can not know which goes around which, the Earth or Sun, and still know the truth of the statement “The government should stop telling people how to live their lives.” He can be as wrong as can be about how lasers work (another question asked) and still know the lunacy of this statement: “Government should put limits on the choices individuals can make so they don’t get in the way of what’s good for society.”

This just goes to show you how useless science knowledge is to most folks, but how important political and moral knowledge is. Would the world really be a better place if all were made to swear to the belief that the Earth orbits the sun? Sure it’s a simple fact, but how useful is it to the average man? Except in answering questions on surveys like this, not much.

And so we end with the non sequitur: O science! Where are you! Why have you left us!

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