Wisconsin Election Statistics

Wisconsin Kathy Nickolaus press conferenceMuch is being made of the election between Republican State Supreme Court Justice Prosser and Democrat Kloppenburg. On election night a quick count of votes was made and released immediately to the media. This count showed Kloppenburg ahead by about 200 votes out of some million-and-a-half cast.

The election was of interest because of the contretemps involving left-leaning state employee unions (who say their members aren’t provided sufficient benefits and who want the right to collectively bargain on this point), a right-leaning Governor (who wants to reduce the state’s deficit by not increasing the state employee benefits as fast as has been done historically), and Democrats in the legislature who fearfully fled the state to forestall legislation.

To emphasize their point, some in the unions, or their supporters, threatened (mostly anonymously) various Republicans with death, destruction, desecration, etc. The media chose not to emphasize the violent nature of these threats, doubtless believing they were not representative, and perhaps because the media recalled their behavior in the Gabrielle Giffords Tucson shooting.

The media instead sought to turn the election into what they call a “national referendum,” which to them meant that this local election was indicative of the mood of the rest of the country. So when it first appeared that Kloppenburg won, the media began running stories claiming victory for Kloppenburg and their referendum.

In spite of media hopefulness, some pointed out that a contest with such a narrow margin was not much of a referendum and was instead an indication that the populace was evenly split.

Then came the press conference from Waukesha County Clerk Kathy Nickolaus who explained that an error had been made and that, after correcting it, Justice Prosser was the victor by some 7,000 votes (via HotAir).

Two things are significant. The method of data collection and the behavior of reporters.

I always tell my students and clients that eighty-percent of any data analysis project is spent in data preparation. Almost universally, people believe that their data is “ready to go”, has no errors, or is otherwise unproblematic. The opposite is nearly always true. Errors abound.

In Wisconsin, they gave Excel spreadsheets to precincts to fill out. The precincts were not supposed to meddle with the spreadsheets except to input data, after which they were to return the spreadsheets to headquarters where they would be read into an Access database. The process was done by hand at each level.

Naturally, some people could not help themselves and added extraneous columns and data into the spreadsheets. This always happens. If you have explicit instructions that the data in a cell can only, under penalty of torture, be coded “Y” or “N”, there will always be found someone who will write “Y but only because…” or “Not sure” or God knows what.

The creativity of humans in lousing up instructions is infinite. So it is no surprise, none whatsoever, that errors were made in Wisconsin, especially in the heat of battle and by clerks anxious to release results to the media.

Some in the media took the updated results like a man, but the dejection in many of their voices was evident when asking Nickolaus “How?” and “Are you absolutely sure…?” Earlier, I argued that all journalists should preface their questions by naming their party affiliation or by admitting who they wanted to win, e.g., “Bob Boberts, ABC, Democrat, Kloppenburg hopeful. Do you think…?”

This begins interrogations on a fair footing. Both the questioner and questionee know who is who, and more importantly, so do the audience. It also saves reporters from having to falsely claim objectivity and thus weaken their souls.

But notice what has happened. By insisting on the national-referendum theme and then prematurely touting it, the press are stuck with it. They are now in the position of saying (perhaps tacitly) that Prosser’s victory is important for the country. The pain many reporters are feeling must be extraordinary.

The vote objectively indicates an even split in the temperament of the populace, just as it did when the media thought Kloppenburg won. Yet that story has been eclipsed by the horse-race referendum, a theme many would have missed had the press not focused so much attention on it. I wonder if they cover this subject in J-school?

If you liked this, you’ll also like this: The California Federation Of Teachers Meet: A Play In One Act.

Chu On These Climate Tipping Points

“Beware the Tipping Point, my son!
That little wee thing, the difference it makes!
Beware its Connector Theory, and shun
Its luminous Balderdash!”

With appropriate apologies to the great logician whose words I abused, we consider the mysterious, misunderstood Tipping Point. Beware! for it is as rare as a Jabberwocky, everywhere lurking and ready to pounce, to devour and overcome. We can but sense its approach, its true shape is camouflaged. We only know that it was here after it has gone. Alas!

Or such is the popular imagination. The truth, as it frequently is, is mundane. Tipping point

In physics, a tipping point is that point in a dynamic system where the system switches from one state of equilibrium to another. Take a cardboard box and flick it with your finger. If the box is light enough, it will wiggle a bit but it will return to its resting state. Now push it over, with one of the edges touching the floor acting as a hinge. Then let go. If you push just a little, the box will return to its original state (perhaps after bouncing around). But there will come a point which if you push past it, the box will fall over. That point is literally and physically the tipping point.

The equations of motion and the physical properties of the box govern the tipping point. And, of course, tipping points are present in many, but not all, physical systems. It’s also important to understand that the mere presence of a tipping point, its theoretical possibility, does not guarantee that this point will ever be reached. Finally, there is no “good” or “bad” about states of equilibrium. Those judgments require reference to non-physical criteria. Whether the box lies on this side or that is only interesting if you have money on the outcome or something breakable inside.

The climate is vastly more complex than a falling box. It is impossible—not just unlikely, but impossible—to model the climate precisely (actually, our expertise is such that we can only model an idealization of a box and not even a real box). We do not and cannot measure the climate well. The best models are gross simplifications where we abandon precision and instead seek to mimic statistical properties of the climate. Even that is a tricky, error-prone business.

A tipping point in the climate is that point at which the system changes from one state of equilibrium to another. It is not, it is certainly not, true that the state into which the system changes is inevitably worse than the previous state. If there are true tipping points in our real climate, passing through one does not in any way imply conditions must become worse. They might, they might not is the best we can say (conditions might even improve).

Secretary of Energy Steven Chu wants climate modelers to overcome their squeamishness and place equations for tipping points into climate models. He said, “To be sure, if you start to model the tipping points you put in much larger uncertainties, but there is a difference between uncertainty and inaccuracy.”

Chu is right that there is a difference between uncertainty and inaccuracy, but his reasoning is flawed. If you add, merely for the sake of adding, tipping points into model equations and those equations do not represent reality you introduce inaccuracy and increase uncertainty. And that is not the worst of it.

If you design a model that includes tipping points, and then run that model, you will likely find that the results evince tipping points. But it would be a mistake to issue the press release, “Tipping Points Found In Climate, Scientists Concerned.” You included the tipping points, it is therefore no shock you found what you included. You audience becomes more certain than it deserves to be.

Why, this is just like building into a model subroutines which provide for a positive feedback on temperature with carbon dioxide. When that model is run, it will show positive feedbacks on temperature with carbon dioxide. Is it worth a press release to say so?

Chu is worried that the “long tail of the damage tail is out there” and that climate models aren’t capturing these statistical properties. It is true that climate models do not (so far) make skillful predictions, thus they cannot adequately assess risk. Whether the risk is actually higher or lower is unknown. Including tipping points in climate models to artificially inflate risk, just to produce fatter “long tails”, is not good science. Modelers are right to be leery of tipping points.

Thanks to Marc Morano for the original link.

Guilty People Aren’t Guilty, Innocent People Are

The man who took the knife and slit the throat of the woman whose money and body he wanted could not help himself. But the judge who sentenced that man to jail for life sure knew what he was doing.

The judge had freedom, he could make a choice. He should have considered that the murderer had none. The murder’s brain made the murderer do what the murderer did (the personal pronoun is out of place here). The judge’s brain was under no constraints. The judge could have let the murder go.

And, no, it’s not that mysterious entity Society which caused the man to wield his knife. That theory is passé! It is so 1970. This is a new century and we’re well into it. Times is modern! We should embrace new and colorful, computer-generated theories of exculpability.

Enter neuroscience and neuroscientists like David Eagleman, who begins with a kernel of truth embedded in hyperbole:

The first lesson we learn from studying our own circuitry is shocking: most of what we do and think and feel is not under our conscious control. The vast jungles of neurons operate their own programs. The conscious you – the I that flickers to life when you wake up in the morning – is the smallest bit of what’s transpiring in your brain. Although we are dependent on the functioning of the brain for our inner lives, it runs its own show. Your consciousness is like a tiny stowaway on a transatlantic steamship, taking credit for the journey without acknowledging the massive engineering underfoot.

From that he moves to two false but fixable statements:

The problem is that the law rests on two assumptions that are charitable, but demonstrably false. The first is that people are “practical reasoners”, which is the law’s way of saying that they are capable of acting in alignment with their best interests, and capable of rational foresight about their actions. The second is that all brains are created equal.

The law is not based on the principle that all are “practical reasoners.” It is based on the principle that people are responsible for their self-directed actions. The law is also not based upon the principle “that all brains are created equal.” The mentally deficient (in the technical sense) are given due consideration.

From these first three (with two false) premises, he announces, “The legal system needs an infusion of neuroscience. It needs to turn away from an ancient notion of how people should behave to understand better how they do behave.” This will not lead to blanket exculpation of those who commit crimes, but to a “refinement of our sentencing” of the guilty.

He concludes, “Currently, our patterns of punishment are founded on the concepts of personal volition and the attendant culpability. But a shift in our understanding of individual differences suggests a move toward prison sentences tailored to the risk of recidivism rather than the desire for revenge.”

This conclusion does not follow from its premises, even assuming they are all true. If we accept that criminals1 (defined as those people who commit a well-defined act) could not help themselves, then locking these people away makes no sense. It is like punishing a snail for leaving a trail of slime.

It frightens me to think that some believe we can predict which criminal will become a recidivist and which not. But assuming we can, then you are introducing the entirely new legal principle that a man should be locked up because some statistical model predicts he will commit a future crime. And why just lock up those who have previously committed crimes? We could apply the same models to everybody and put away any who we predict would commit undesirable acts.

If you assume a criminal could help himself, at least partially, but believe he will not become a recidivist (perhaps he slaughtered his hated father), Eagleman (apparently) argues letting this man go free else his punishment would only be for revenge.

And here we have it, the principle no truly Enlightened person would accept. Instead of revenge, “It is time to let go of our intuitions about how people should behave and pay attention to how they do behave – to run our legal system as rigorously as a science experiment.”

Eagleman, who evidently has no acquaintance with John Locke, has not considered that it was the evolution from personal and family vendettas and blood feuds, to disinterested judges and punishment by the state which gave us civil society. Prison is not revenge, it is the rule of law. It is justice.

—————————————————————————————-

1Why just criminals? We all have brains and so are all slaves to our neurons to some extent. We could reorder all of society on firm, neurological grounds. What happiness awaits!

Climate Science And Significance: Wall Street Journal Takes On Statistics

Coin Flips and Dice Rolls

Doug Keenan has a must-read piece in the Wall Street Journal on the time series analysis of global temperature (Thanks to Randy, Roger, and John for the links).

I differ from Keenan on the value of “significance” (see the next story), but that difference makes no difference here. Significance or lack of it isn’t the real story: the model that represents our uncertainty in the temperature is.

Something caused the temperature to take the values it did. That something is the physics of heat and radiative transfer and so forth, processes so complicated that no climate model has come close to reproducing the observed values of temperature (climate models have produced simulations that mimic certain statistical properties of the observed values, which is not at all the same thing).

Since the physics is unworkable, climatologists turn to statistics—always a dangerous ploy. This is because there are an infinite number of statistical models that can reproduce the observed values of the time series. Most of these models will be useless, however, in predicting not-yet-observed values of the time series. Even worse, the decision of “statistical significance” changes with the model. Using one model, the data is “statistically significant”; use another it is not. See Doug’s article for how this works for the global temperature series.

Want the best kept secret in statistics? You can always—as in every single time without exception—find a model which says your data is “statistically significant.” That model will almost certainly be worse than useless in predicting new data, though. If your model is correct, it ought to be able to predict new data, the only true test of model correctness.

But if people aren’t asking about predictions (and most don’t) and merely want to know if their belief about what might have caused the data to take the values it did, then you can always pronounce your belief “statistically significant,” because you can always find a model that produces “significance.”

It turns out for temperature data one very simple model says “Significant!”, but other, more complex models, say “Not significant.” Again, this is no surprise: this will always be true regardless of the data. But the model used by the IPCC is a very simple and not very realistic one. Keenan finds other models that fit better and that pass certain rule-of-thumb tests time series modelers use.

Keenan isn’t claiming his model is certainly right and the IPCC’s is certainly wrong. But it is clear that the IPCC was not especially vigorous in investigating plausible alternatives. And why should they? They had their “significance”, which is all they really wanted.

Supreme Court Statistics

Read Carl Bialik’s Wall Street Journal piece “Making a Stat Less Significant“, about how the question of statistical significance has reached the Supreme Court of these fine United States.

In a case before the court the justices said

companies can’t only rely on statistical significance when deciding what they need to disclose to investors.

Amen, say several statisticians who have long argued that the concept of statistical significance has unjustly overtaken other barometers used to determine which experimental results are valid and warrant public distribution. “Statistical significance doesn’t tell you everything about the truth of the hypothesis you’re exploring,” says Steven Goodman, an epidemiologist and biostatistician at the Johns Hopkins Bloomberg School of Public Health.

A point on which most statisticians agree is that statistical significance is difficult to explain.

I’ll echo that Amen, brother Goodman. Statistical significance does not indicate the truth or falsity of the hypothesis you’re exploring. Instead, it tells you the probability of seeing the value of an hoc statistic larger than the one you actually saw given you make some rather curious assumptions about the probability model used. And, most crucially, given the model used is true (see the story above).

The question here was, “Does this drug produces harmful side effects?” Bayesian statistics can answer that question, or at least put a probability value on it, but frequentist statistics (which uses statistical significance as a measure) must remain mute.

The story of how a philosophy of evidence that can’t answer direct questions came to dominate science is fascinating. Regular readers will already know the answer, but newcomers will want to click on the Stats/Climate link at the top of the page and read the relevant articles.

Thanks to Bernie and several other readers who provided this link.

California Air Resources Board Uses Strange Statistics, UCLA Fires Scientist

The story (related in full at HotAir.org) is long and tangled, but the short version is this.

The California Air Resources Board (CARB) wanted to regulate diesel truck fumes, inherently believing them bad. So it sought the guidance of CARB employee Hien Tran, a fellow who received a PhD in “Applied Statistics” after sending in the proper number of Captain Crunch cereal boxtops (plus $1,000 smackeroos) to Thornhill University (“75 years of active contribution to human knowledge and higher education”1).

Yet somehow Tran forgot his degree’s origin and told his employers it came from UC Davis. It must have been the same sort of mental defect which allowed Tran to lead-author a paper which “proved” that diesel trucks caused “2,000 premature deaths” per year in the most populous left coast state. I remind readers that cause is a strong word.

This was the scientific evidence CARB needed. New regulations and rules and bureaucratic oversight and fees and requirements and forms and inspections and much more was passed into law. All was well.

Meanwhile, James Enstrom, an environmental sciences professor and researcher at UCLA, who went through the old-fashioned process of earning his PhD, wrote his own paper which said that diesel fumes and deaths had no relation. Since Enstrom reviewed every possible source, he wondered how Tran could come to the opposite conclusion using the same data.

This was how Enstrom discovered Tran to be a liar. He dutifully relayed his discoveries about Tran and his own published work to CARB who proceeded to—wait for it—ignore it. That’s not quite true. They set it aside until after they had passed the new regulations, after which the CARB Chairman Mary Nichols (a lawyer) admitted Tran’s fraud. But the new regulations were already law. What more could she do?

Tran received a fine and demotion but kept his job (and cushy California retirement package). Via open disclosure laws, California has released Tran’s disciplinary letter, in which it states the State stands by Tran’s results (“both their methodology and the rigorous peer and scientific review process”), though the State admonishes him for lying about his credentials. Tran does have a Master’s in statistics from UC Davis and did begin the PhD program there, but dropped out. His PhD advisor was contacted and said he had no idea what became of Tran.

Enstrom’s bosses at UCLA did not appreciate his meddling into settled science (we imagine he was told “The debate is over”) and so they fired him. Yet before Enstrom’s “controversial” work was generally known, UCLA School of Medicine Assistant Dean for Academic Affairs Richard H. Gold was able to say, in an Entrom’s annual review, “Dr. Enstrom’s research is fully aligned with the department’s mission.”

But after Enstrom complained about Tran and CARB, UCLA fired him saying Enstrom’s “research failed to accord with the department’s mission.” Surely coincidentally, Chairman Nichols and the second-ranking member of CARB are also UCLA professors.

The Foundation for Individual Rights in Education (FIRE) took Enstrom’s case and has asked UCLA to reinstate Enstrom. FIRE’s website has a trove of documents on the matter.

UCLA, being a “UC”, receives a bunch of money from the State of California, including various grants and contracts from CARB. UCLA’s decision to fire Enstrom could not have been easy. They had to balance the need for integrity and the need for cash flow. With an enormous number of administrators, each with large staffs (I believe they outnumber full-time professors), UCLA could not afford to let the flow become a trickle. Thus, regardless of whatever other reasons they had, UCLA at least did the fiscally responsible thing.

——————————————————————-

1Intriguingly, their site is no longer up; I used Google Cache to retrieve the quote. Whois tells us the site belongs to Thornhill University at 155-8171 Yonge Street, Thornhill, Ontario L3T 2C6. It is administered by Fariba Mosleh, faribamosleh@yahoo.com. I emailed Mosleh to ask whether Tran’s case had anything to do with the site closing. I did not receive a reply.

I Am The Cause Of All Discrimination In The United States Of America

Today’s post is at Pajama’s Media, “The Cause of All Discrimination? Me: One man makes a shocking confession.

Logically, if there is discrimination, there must be discriminators and discriminatees. Who, then, are the vile discriminators? The newly released Census data can tell us.

Pajamas Media

The Census has released its figures. The latest count is 308,745,538 citizens living within these Disunited States. I say “Disunited” not to pun but because it is well-known that discrimination is rampant within our tumultuous borders. The problem is so awful and so sickeningly pervasive that we are anything but united.

Females of the opposite sex outnumber males by 51 to 49 percent. Females cannot discriminate, but can be discriminated against. This is true by law (in most localities). Thus, there are only 157,460,224 potential discriminators, all male.

The rest is here. It might be easier to answer comments there (thanks!).

Thanks to David Steinberg, editor at PJM.

Education: A Vaccine Against Ignorance? Or, There Are Too Many People!

“Currently, one could argue that the most significant form of global pollution is human population growth.” So says Mr Jack Trevors, Editor-in-Chief of Water, Air, & Soil Pollution (WASP), “an international, interdisciplinary journal on all aspects of pollution and solutions to pollution in the biosphere. This includes chemical, physical and biological processes affecting flora, fauna, water, air and soil in relation to environmental pollution.”

WASP insists on rigorous peer review: “Articles should not be submitted that are of local interest only and do not advance international knowledge in environmental pollution and solutions to pollution. Articles that simply replicate known knowledge or techniques while researching a local pollution problem will normally be rejected without review.”

So what are we to make of the peer-reviewed article “A Vaccine Against Ignorance?” by Trevors and Associate Editor Mr Milton Saier?

It begins by echoing d’Holbach: “One of the greatest challenges facing humanity is ignorance.” This keystone of Enlightenment philosophy promises that once man is properly educated he will live in paradise. However, it is with sadness that I report that this discovery, of obvious monumental importance, has the bloody empirical corollary, “If a man refuses education he must be extirpated lest he spread the cancer of ignorance.”

What can Trevors and Saier teach mankind?

[T]he capitalistic systems of economy follow the one principal rule: the rule of profit making. All else must bow down to this rule…The current USA is an example of a failed capitalistic state in which essential long-term goals such as prevention of climate change and limitation of human population growth are subjugated to the short-term profit motive and the principle of economic growth.

The word “failed” is curious until we hear their lamentation that “many people in the USA” are “confused” about the unbearable “truth of human-caused Global Warming.” Confused is comforting because confusion can be repaired by education. And nowhere is there more misunderstanding than about global warming whose “theoretical basis was established over 50 years ago!” 50! If only we could educate the befuddled, the rise of the oceans would begin to slow, the planet would begin to heal.

Alas, the ignorant “are likely to prefer a fairy tale to reality; it’s so much nicer (for a while) to think that no serious problems exist. Such people just continue to live in a fantasy world that will dissolve when reality becomes oppressive, just as does a dream fades [sic] away after one wakes.” But by then it will “be too late to correct the problems that were propagated by ignorance” (this tortuous metaphor appears to argue that the citizenry should remain aslumber1).

Only the panacea Education can cause the ignorant to develop “a deep feeling of compassion and responsibility towards all, a feeling of dedication to the welfare of humans and other beings on the planet.” We must not yield “to the greedy interests of profiteers! Unless the impediments that prevent people from gaining the educations they desire are overcome, we will remain intellectual barbarians.”

Wait: how can the ignorant desire the education they lack? Are they not asleep? Are they not wallowing in their greed and self-centeredness? Never mind: education is what counts, education is all. Education cures “insecure” urges to “spend excessively on military”.

This isn’t some random non sequitur, no sir! See, every dollar a country spends on “weapons of destruction” is one they could have invested on “means to limit their population”. The educated know that people are the cause of misery; therefore, limiting people reduces misery.

What’s needed is obvious: more education. But coupled with “restrictions on people, agencies, and corporations determined to follow the profit motive, and in so doing, undermine the intelligence of the populace.” And you thought Steve Jobs, head of Apple corporation, was benign. Cut out the cancer!

With the steel-handed education championed by our authors, “ignorance would fade into the background, and discrimination, racism, intolerance, terrorism, crime, and fraud would be countered by the larger more rational segments of the human population.” Trevors and Saier are not, they are certainly not, “suggesting the resurrection of a utopian wish.” Yet something approaching bliss can be had when “inferior ideas and thoughts in ignorant human minds are eliminated from the equation and replaced with superior ideas resulting from a sound education.” Eliminated!

Brothers and sisters, ladies and gentlemen, let us “submerge our selfish desires for the betterment of humanity and the planet.” Can I get an amen?

Update

Our caring pair also have published “We do not have a spare Earth ” in the science journal Environmentalist, in which they take great pains to say, repeatedly and with scintillating emphasis, “We do not have a spare Earth.” More science: “The living organisms including humans in our common biosphere follow a simple set of rules. Some organisms live and reproduce, some live and do not reproduce and some die before they reproduce.” Because of their glamorous and demanding careers, many statisticians fall into that last category.

——————————————————————————–

1No, but it’s a word now.