William M. Briggs

Statistician to the Stars!

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Summary Against Modern Thought: Periodic Review

This may be proved in three ways. The first...

This may be proved in three ways. The first…

See the first post in this series for an explanation and guide of our tour of Summa Contra Gentiles. All posts are under the category SAMT.

Let’s catch up so that we’re not in danger of forgetting where we came from, where we are, and where we’re going. I do not mean here to give complete arguments. That has already been done in the original posts. What follows is only a sketch to reorient and reinvigorate us. Don’t be lazy.

Does God exist? How do we know? Given the logical implications of answering those questions, how do we explain what can we know about God? What can we know about God? Well, some things, but not every thing. But more than you’d guess. These questions, all worthy and deserving of our attention, form the discourse of Book One of SCG. Let’s review.

Our efforts will not be in vain. From Chapter 3: “Now in those things which we hold about God there is truth in two ways. For certain things that are true about God wholly surpass the capability of human reason, for instance that God is three and one: while there are certain things to which even natural reason can attain, for instance that God is, that God is one, and others like these, which even the philosophers proved demonstratively of God, being guided by the light of natural reason.”

Let’s don’t be lazy; let’s attack each point assiduously, as argued in Chapter 4. Why? Because “the checking of presumption which is the mother of error” Chapter 5. Repeat that thrice. Most of what we believe is given to us. Let’s think things through, guided by those of superior intelligence. God is an embarrassing subject for our world, except to denigrate religion or sneer at theology, these unthinking irrational ill-educated attitudes being thought a mark of sophistication. Don’t be lazy.

The proof, using only reason and not a whit of divine revelation (beyond that which we all possess) which forms the backbone of Aquinas’s efforts, is that of first motion, which begins in Chapter 13 (part 2, part 3, part 4, part 5; don’t be lazy).

3 The first way is as follows. Whatever is in motion is moved by another: and it is clear to the sense that something, the sun for instance, is in motion. Therefore it is set in motion by something else moving it. Now that which moves it is itself either moved or not. If it be not moved, then the point is proved that we must needs postulate an immovable mover: and this we call God. If, however, it be moved, it is moved by another mover. Either, therefore, we must proceed to infinity, or we must come to an immovable mover. But it is not possible to proceed to infinity. Therefore it is necessary to postulate an immovable mover.

This simple and quite beautiful eminently reasonable and (thus far?) irrefutable argument has never stopped being misunderstood. Aquinas, and we following him, went to great pains to show that this movement is here-and-now. That which accounts for how any movement, which is to say how any change, happens must be because of a First Mover, an Unchanging Changer.

From this argument we learned (among other things) the concepts of act and potential. Something actual changes a thing from one “state” to another “state”, which before the change was only a potential. It cannot be the potential that is an efficient cause, it must be something actual.

What follows from this is that, because for any and all change there must be a First Changer, that God is not only “everywhere”—but not in the pagan sense; in the sense that if God did not exist, the universe would immediately cease—but God is also eternal, outside time, because time is the measure of movement, and God is Unmoving, Chapter 15. Few of these terms carry the same colloquial definitions we ordinarily carry, so don’t be lazy: read the original argument.

Another consequence is that God does not have any passive potentiality, Chapter 16.

2 For everything in whose substance there is an admixture of potentiality, is possibly non-existent as regards whatever it has of potentiality, for that which may possibly be may possibly not be. Now God in Himself cannot not be, since He is eternal. Therefore in God there is no potentiality to be

Not surprisingly, from these we learn that God is not made of matter. He is not physical stuff, Chapter 17. God is not the god of the atheists; He is not a clever, long-lived alien being composed (say) of energy fields. God is beyond matter: He is spirit.

It immediately follows that God is not made of parts, that he is “simple”, Chapter 18.

1 For in every composite thing there must needs be act and potentiality: since several things cannot become one simply, unless there be something actual there and something else potential. Because those things that are actually, are not united except as an assemblage or group, which are not one simply. In these moreover the very parts that are gathered together are as a potentiality in relation to the union: for they are actually united after being potentially unitable. But in God there is no potentiality. Therefore in Him there is no composition.

Another consequence: there is nothing in God against Nature, Chapter 19, and that God is not a body, Chapter 20, the simplest demonstration of which is, “For since every body is a continuous substance, it is composite and has parts. Now God is not composite, as we have shown. Therefore He is not a body.”

This brings us up to date. God exists, is responsible for the universe remaining in existence and is the ultimate cause of all change, that He is eternal, that He has no potential, that He is not made of stuff and is not a body. Well, fine. But that doesn’t tell us much. This could all describe the some kind of weird immaterial physical uber-field. Though we’ve gone a great distance, we haven’t really done much. We haven’t come close to describing God in full.

But we still have 80 chapters to go! Don’t be lazy.

The Strange Case Of Robert F. Kennedy Jr: Or, Jail Climate Deniers!

No, this isn’t a shooting-fish-in-a-barrel take-down of yet another bug-witted politician who has stayed long past his expiration date. We’re after something deeper today.

Here in a piece (“What States’ Attorneys General Can Do About Climate Deniers”) under his name at the ultra-left Huffington Post (running a curiously old picture of the man), is Kennedy’s opening:

Hysterics at the right-wing think tanks and their acolytes at The Washington Times, talk radio and the blogosphere, are foaming in apoplexy because I supposedly suggested that “all climate deniers should be jailed.”…Of course, I never said that. I support the First Amendment which makes room for any citizen to, even knowingly, spew far more vile lies without legal consequence.

Well, technically he’s right. He never said “all”, but here is a link to a video which has him (at the People’s Climate March) calling for the invention of new laws, and prosecution under old ones, including “treason”, of so-called deniers. Depends on all the meanings of all, I suppose.

He continues:

I do, however, believe that corporations which deliberately, purposefully, maliciously and systematically sponsor climate lies should be given the death penalty. This can be accomplished through an existing legal proceeding known as “charter revocation.” State Attorneys General can invoke this remedy whenever corporations put their profit-making before the “public welfare.”

He slips in “death penalty”, allowing his dimmer readers (this is the Huffington Post) to infer he means it in its literal, cut-their-throats sense. Only later does he reveal it’s a euphemism for some obscure law which has the power to unincorporate corporations. So not real death, but slow asphyxiation by the removal of the means of livelihood. After this legalese is forgotten, he slips in at the end with, “The notion that a State Attorney General might actually execute one of these villains is not a pipe dream.”

His charge:

For over a decade, petroleum industry behemoths led by Koch Industries and ExxonMobil, have waged a successful multi-million dollar propaganda blitz to mislead the public about global warming using the same techniques honed by Big Tobacco in its campaign to hoodwink the public about smoking.

It never does any good to tell people that you get nothing or next to nothing for your work in skeptical climate science (my total, from all sources, is fast reaching double digits). They don’t believe it. No, it’s worse than that. It’s like telling a UFO hunter that the government isn’t engaged in a secret cover-up. Of course you would deny the cover-up! That means there’s a cover-up!

Next week, in a review of Alex Epstein’s forthcoming The Moral Case for Fossil Fuels, we’ll learn the opposite of Kennedy’s charge is true: that oil companies have done everything except abandon oil in order to conform publicly to Kennedy’s religion.

And how much money does Big Green—Greenpeace, Sierra Club, the federal government through the EPA, USDA, etc.—pump into the system? I’ve seen many estimates, but by any count the amount dwarfs what skeptics receive.

Kennedy mentions some “culprits”, like Cato and Heartland, and says:

Like the Tobacco Institute and CTR, these front groups are snake pits for sociopaths. Run by venomous carbon industry toadies, they stable a craven menagerie of propaganda wizards, slick biostitutes, tobacco scientists, snake oil hucksters, voodoo economists and other so-called “experts” employed to publish beguiling studies, appear on TV and radio, and write deceptive articles critiquing the “flawed science” predicting climate change.

I have to admit liking that last sentence, though I haven’t any idea what a “biostitutes” is. We have seen time and again that “believers” like Kennedy have almost no understanding of climatology. They couldn’t define, say, a sigma coordinate system to save their lunches, let alone their lives. There is complete mystification over what convective available potential energy could mean. To them, the satellite inverse problem sounds like a vague oxymoron.

But it doesn’t matter. Belief is all they are after, and belief is what they get. Their belief is raw, primal. We’ve seen enough to know that environmentalism is pure religion, based on the false and ridiculous idea that Nature somewhere exists in its pristine, non-human state.

This is why questions are heresy, why Kennedy can foolishly call for his enemies to be jailed or executed. This deluded man isn’t the only one. Here is an abbreviated list of enviro-worshippers full of bloodlust: here, here, here, here.

Nature—a living god—must be appeased.

So the real question for discussion is, not the state of Kennedy’s sanity, but how this religion will progress. Ideas?

Stephen Hawking Thinks Too Much Of Us; More

These people are reading.

These people are reading.

Autumn of the Modern Ages

What!? You haven’t headed over to Mike Flynn’s place and read his series The Autumn of the Modern Ages? Sometimes I don’t understand you people at all.

The decline of the book goes hand in hand with the decline of the bourgeois. Considered reflection requires time, silence, logic, and thinking in depth. But post-modern media — we cannot call them books any longer — are oriented to “brevity, speed, change, urgency, variety, and feelings.” This would be very dangerous to democracy, but in a future dominated by extended adolescence, we might not miss that too much. We will always have the sputtering fuse.

The only remaining god in the West will be the symbiotic Me-State beast.

Update Proof of that last claim. Louisiana State University introduces new LGBT minor, from which “Krebsbach, who identifies as a cisgender lesbian…” Identifies.

Hawking Says Not God

The man never tires of doing bad philosophy, and has reiterated his disbelief in God. We postmoderns say, Whatever.

“Religion believes in miracles, but these aren’t compatible with science.” Proof, please? Nah. Just bluster.

Skip it. The thing that caught my eye was this: “In my opinion, there is no aspect of reality beyond the reach of the human mind.” So speaks a research professor who never had to teach statistics classes to people who did not want to take statistics.

Any experience with actual human beings is enough to prove that there is much beyond the reach of the human mind. We can, for instance, never know the mind of God. We can never know what infinity is like. We can never know everything, even collectively. We can never know how things which are necessarily true are necessarily true (Hawking, disdaining philosophy, does not know this). And so on.

Again, perhaps this is the postmodern in us which no longer sees the sky as the limit. That destination now seems much closer to the ground.

16-year-old Voters

They did it in Scotland, so why not here? Why not everywhere? So argues Jason Brennan, “assistant professor of strategy, economics, ethics and public policy at Georgetown University.” His thrusts backwards:

The trouble is that the main reason most people cite for barring 16- and 17-year-olds from voting looks like an equally good reason to stop most American adults from voting, too.

Amen, brother. But the cuts the other way, too, and says that we ought to pare back voting privileges. The closer we get to a true Demos, where everybody votes on everything, the closer we get to madness because the collective mind is shockingly easy to sway in the short term.

Proof? This headline: “Poll: 51% of Democrats support criminalizing hate speech” The implications are so obvious, I will not insult you by stating them.

Bad Medicine

This link no longer works. Sorry.

. Labos doesn’t come to the full realization, but he gets many things right. See especially the part on Exaggerated Risks.

Gerd Speaks

I like this Gerd Gigerenzer guy, and he has things to learn in his essay “Scientific Inference Via Statistical Rituals.

Sir Ronald Fisher, to whom it has been wrongly attributed, in fact wrote that no researcher should use the same level of significance from experiment to experiment, while the eminent statisticians Jerzy Neyman & Egon Pearson would roll over in their graves if they knew about its current use. Bayesians too have always detested p-values.

Detestation is right. But the real kicker is here:

I do not mean to throw out the baby with the bathwater and get rid of statistics, which offers a highly useful toolbox for researchers. But it is time to get rid of statistical rituals that nurture automatic and mindless inferences.

Scientists should study rituals, not perform rituals themselves.


Dover Beach

You might have seen his comments from time to time. He has a new bookmarkable site The Ordeal of Consciousness, with articles like “Scruton and Taylor on the Secular and the Sacred”, “Mathematics and the Order of the World” (did you buy a copy of Franklin’s book? It’s outrageously expensive!).

C.S. Lewis’s Epistemology

Brandon Vogt has a video of a lecture by “Union University philosophy professor Justin Barnard, who makes two relatively bold claims: first that Lewis was probably not the greatest Christian apologist of the twentieth century, as many Protestants and Catholics believe, and yet he probably was the greatest Christian epistemologist of the twentieth century.”


Boing Boing has a fun article: Making better use of dice in games, about a game developer who takes the “randomness” out of dice games.


I got bit by one on the tip of my right ear. I want sympathy. Hasn’t stopped itching in hours.

The True Meaning Of Statistical Models

It's catching.

It’s catching. (Image source.)

This came up yesterday (again, as it does often), so I figure one more stab is in order. Because the answer isn’t simple, I had to write a lot, which means it won’t get read, which means I’ll have to write about it again in the future.

Trust your eyes

You’re a doctor (your mother is proud) and have invented a new pill, profitizol, said to cure the screaming willies. You give this pill to 100 volunteer sufferers, and to another 100 you give an identically looking placebo.

Here are the facts, doc: 71 folks in the profiterol group got better, whereas only 60 in the placebo group did.

Now here is what I swear is not a trick question. If you can answer it, you’ll have grasped the true essence of statistical modeling. In what group were there a greater proportion of recoverers?

This is the same question that was asked yesterday, but with respect to the global temperature values. Once we decided what was meant by a “trend”—itself no easy task—the question was: Was there a trend?

May I have a drum roll, please! The answer to today’s question is—isn’t the tension unbearable?—more people in the profitizol group got better. The answer to yesterday’s question was (accepting the definition of trend therein): no.

These answers cause tremendous angst, because people figure it can’t be that easy. It doesn’t sound sciency enough. Well, it is that easy. You can go on national television and trumpet to the world the indisputable inarguable obvious absolute truths that more people in the drug group got better, and that (given our definition of trend) there hasn’t been a trend these twenty years.

Question two: what caused the difference in observed recovery rates? And what caused the temperature to do what it did?

My answer for both: I don’t know. But I do know that some thing or things caused each person in each group to get better or not. And I know that some thing or things caused temperature to take the values it did. I also know that “chance” or “randomness” weren’t the causes. They can’t be, because they are measures of ignorance and not physical objects. Lack of an allele of a certain gene can cause non-recovery, and the sun can cause the temperature to increase, but “chance” is without any power whatsoever.

Results are never due to chance, they are due to real causes, which we may or may not know.

The IPCC claims to know why temperature did what it did. We know the IPCC is wrong, because their model predicted things which did not happen. That means the causes it identified are wrong in some way, either by omission or commission. That’s for them to figure out.

Clever readers will have noticed that, thus far, there was no need for statistical models. But if our goal was only to make the statement which group got better at greater rates or if there was a trend, no model was needed. Why substitute perfectly good reality with a model? That is to commit the Deadly Sin of Reification (alas, an all too common failing).

Enter the models

The classically trained (Bayesian or frequentist) statistician will still want to model, because that is what statisticians do. In the drug trial they will invent for themselves a “null hypothesis”, which is the proposition, “Profitizol and the placebo cause the exact same biological effects”, which they ask us to “accept” or “reject”.

That means, in each patient, profitizol or a placebo would do the same exact thing, i.e. interact with the relevant biological pathways associated with the screaming willies such that no measurement on any system would reveal any difference. But given you are a doctor, aware of biochemistry, genetics, and the various biological manifestations of the screaming willies, it is highly unlikely this “null” proposition holds. Indeed, to insist it does is to abandon or willfully ignore all this knowledge and cast all your attention on only that which can be quantified (the Sin of Scientism).

Of course, you might have made a mistake and created a substance which was (relative to the SW) identical with the placebo. Mistakes happen. How do we tell? Do we have any evidence that profitizol works? That’s the real question, the question everybody wants to know. Well, what does “works” mean?

Uh oh. Now we’re into causality. If by “works” we mean, “Every patient that eats profitizol is cured of the SW” then profitizol does not work, because why? Because not every patient got better. If by “works” we mean, “Some patients that eat profitizol are cured of the SW” then profitizol works, and so does the placebo, because, of course, some patients who ate the drug got better. Defining properly what “works” is not an easy job, as this series of essays on a famous statistical experiment proves. Here we’re stuck with the mixed evidence that patients in both groups got better. Clearly, something other than just interacting with a drug or placebo is going on.

What to do?

Remember the old saw about how the sale of ice cream cones was “correlated” with drownings? Everybody loves to cite—and to scoff at—this example because it is obviously missing any direct causal connection. But it’s a perfectly valid statistical model. Why?

Because a statistical model is only interested in quantifying the uncertainty in some observable, given clearly stated evidence. Thus if we know that ice creams sales are up, it’s a good bet that drownings will rise. We haven’t said why, but this model makes good predictions! (I’m hand-waving, but you (had better) get the idea.)

Statistical models do not say anything about causality. We’re not learning why people are drowning, or why people are getting better on profitizol, or why the temperature is doing what it’s doing. We are instead quantifying our uncertainty given changes in certain conditions—and that is it.

If we knew all about the causes of a thing, we would not need statistics. We would feed the initial and observed conditions into our causal model, and out would pop what would happen. If we don’t know the causes, or can’t learn them, but still want to quantify uncertainty, we can use a statistical model. But it’s always a mistake to infer (without error; logically infer) causality because some statistical model passes some arbitrary test about the already observed data. The ice cream-drowning model (we assume) would pass the standard tests. But there is no causality.

Penultimate fact: To any given set of data, any number of statistical or causal or combination models can be fit, any number of which fit that observed data arbitrarily well. I can have a model and you can have a rival one, both which “fit” the data. How do we tell which model is better?

Last fact: Every model (causal or statistical or combination) implies (logically implies) a prediction. Since models say what values, or with what probability what values, some observable will take given some conditions, all we do is supply those conditions which indicate new circumstances (usually the future)—voilà! A prediction!

It’s true most people who use statistical models have no idea of this implication (they were likely not taught it). Still, it is true, and even obvious once you give it some thought.

Not knowing this implication is why so many statistical models are meager, petty things. At least the IPCC stuck around and waited to see whether the model they proposed worked. Most users of statistics are content to fit their model to data, announce measures of that fit (and since any number of models will fit as well, this is dull information), and then they run away winking and nudging about the causality which is “obvious.”

Not recognizing this is why we are going through our “reproducibility crisis”, which, you will notice, hits just those fields which rely primarily on statistics.

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