William M. Briggs

Statistician to the Stars!

Page 152 of 736

Drudge, Rush, Gaia, The Pope, Radio, Etc.


Busy week. To say the least. Class ends this weekend, and it gets busier as it progresses.

I had no idea that the piece I wrote yesterday on The Stream—The Scientific Pantheist Who Advises Pope Francis—would garner the attention it did. It made Drudge—“Pope’s key science advisor is atheist who believes in ‘Gaia, not God’…”—and Rush Limbaugh. I found out the latter when I started receiving texts in the noontime from excited friends.

You and I, dear Reader, are well accustomed to smelly science. The dissecting of rotten research is daily bread for us. So I thought not much of taking apart a paper or two more. But for the first time it was noticed on a larger scale. True, it was because this time it was political. So I expect interest to drop off after the next thing becomes important. Too bad, because the most of the science barrel is rotten, as we know.

And then came the radio shows. I did two yesterday (was it two or three?), two the day before, etc., and I have two scheduled for today:

TIME: 7:20 — 7:30AM (ET)
HOST/SHOW: Scott Voorhees / The Scott Voorhees Show
STATION: KFAB 1110AM — Omaha, NE

TIME: 9:35 — 10:00AM (ET)
HOST/SHOW: Bobby Gunther Walsh / Gunther
STATION: WAEB 790AM — Allentown, PA

and others scheduled later, mostly notably

DATE: Tuesday, June 30th
TIME: 4:30 — 4:45PM (ET)
HOST/SHOW: Mike Savage / The Savage Nation
STATION: Nationally Syndicated.

And others are in the works; perhaps, I’ve been told, even TV.

Yet this will soon fade and something else will become important and we can get back to discussing the nature of causality, and why realist epistemology is the only philosophy that kicks butt (the others only imagine they can).

Meanwhile, I’m about 500 emails behind, and more coming. So if you sent one and I haven’t got to it, please forgive me. Please also forgive the brevity of this post.

Here’s a quote from the Limbaugh transcript:

My friends, not one to let things go, I have dug deep, and I have found out practically everything there is to know about the science advisor to Pope Francis on this encyclical. And the main thing you need to know, the guy’s an atheist. The word for it in the story that I found, one of the most credible stories, is a pantheist, which is a variation of atheist. A pantheist is somebody that believes the earth is a living organism that has the equivalent of a brain and reacts to horrible things done to it by humans…

Yesterday, I was on the same Vicki McKenna show Father Z mentions. Not the same time as Bishop Morlino; different day. But McKenna’s show. There may be an eventual link to the recorded version here.

The Stream: The Scientific Pantheist Who Advises Pope Francis


Today’s post is at The Stream, “The Scientific Pantheist Who Advises Pope Francis: The scientist who influenced Laudato Si, and who serves at the Vatican’s science office, seems to believe in Gaia, but not in God.

St. Francis of Assisi’s hymn Laudato Si’ spoke of “Brothers” Sun and Fire and “Sisters” Moon and Water, using these colorful phrases figuratively, as a way of praising God’s creation. These sentimental words so touched Pope Francis that he named his encyclical after this canticle (repeated in paragraph 87 of the Holy Father’s letter).

Neither Pope Francis nor St. Francis took the words literally, of course. Neither believed that fire was alive and could be talked to or reasoned with or, worse, worshiped. Strange, then, that a self-professed atheist and scientific adviser to the Vatican named Hans Schellnhuber appears to believe in a Mother Earth.

Go there to read the rest.

Update I’ve been told the article was linked on Drudge. Thank God for that.

Randomness And The “Null” Hypothesis


Last week of teaching!

Randomness is not a cause. Neither is chance. It is always a mistake to say things like “explainable by chance”, “random change”, “the differences are random”, “unlikely to be due to chance”, “due to chance”, “sampling error”, and so forth. Mutations in biology are said to be “random”; quantum events are called “random”; variables are “random”. An entire theory in statistics is built around the erroneous idea that chance is a cause. This theory has resulted in much grief, as we shall see.

Flip a coin. Many things caused that coin to come up heads or tails. The initial impetus, the strength of the gravitational field, the amount of spin, and so on. If we knew these causes in advance, we could deduce—predict with certainty—the outcome. This isn’t in the least controversial. We know these causes exists; yet because we might not know them for this flip does not imbue the coin with any magical properties. The state of our mind does not effect the coin in any, say, psychokinetic sense.

Pick up a pencil and let it go mid air. What happened? It fell, because why? Because of gravity, we say, a cause with which we are all familiar. But the earth’s gravity isn’t the only force operating on the pencil; just the predominant one. We don’t consider the pencil falling to be “random” because we know the nature or essence of the cause and deduce the consequences. We need to speak more of what makes a causal versus probabilistic model, but a man standing in the middle of a field flipping a coin is thinking more probabilistically than the man dropping a pencil. Probabilities become substitutes for knowledge of causes, they do not become causes themselves.

The language of statistical “hypothesis testing” (in either its frequentist or Bayesian flavor with posteriors or Bayes factors) is very often used in a causal sense even though this is not the intent of those theories. We must acknowledge that the vast majority of users of models of uncertainty think of them in causal terms, mistakenly attributing causes to variously ad hoc hypotheses or to “chance.”

Suppose the user of a model of income has input race into that model, which occurs in two flavors, J and K. The “null” hypothesis will be incorrectly stated as “there is no difference” between the races. We know this is false because if there were no difference between the races, we could not be able to discern the race of any individual. But maybe the user means “no difference in income” between the races. This is also likely false, because any measurement will almost surely show differences: the measured incomes of those of race J will not identically match the measured incomes of those of race K. Likewise, non-trivial functions of the income, like mean or median, between the races will also differ.

If the observed differences are small, in a sense to be explained in a moment, the “null” has been failed to be rejected; it is never accepted. Why this curious and baffling language is used is because of Popper’s notions of falsifiability, which we have discussed before. For now, all we need know is that small (but actual differences) in income will cause the “null” to be accepted. (Nobody really thinks in terms of failing to reject, despite what the theory says.) When the “null” is accepted it is repeated that there is “no” difference between the races, or that any differences we do see are “due to”, i.e. caused by, chance.

But chance isn’t a cause. Chance isn’t a thing. There is no chance present in physical objects: it cannot be extracted nor measured. It cannot be created; it cannot be destroyed. It isn’t an entity. The only possible meaning “due to chance” or “caused by chance” could have is magical, where the exact definition is allowed to vary from person to person, depending on their fancy.

Some thing or things caused each person measured to have the income he did. Race could have been one of these causes. An employer might have looked at an employee and said to himself, “This employee is of race K, therefore I shall increase his salary 3%.” Or he might not have said it, but did it anyway, unthinkingly. Race here is a partial cause. This kind of partial cause might have happened to some, none, or all of the people measured. If the researcher is truly interested in this partial cause, then he would be better served to interview whoever it is that assigns salaries and so discover the causes in each case. Assuming nobody lies or misremembers and can bring themselves to proper introspection, this is the only way to assign causes. But that is time consuming and expensive. And researchers have anyway been falsely taught that if certain statistical thresholds are crossed, causality is present. This fallacy is the cause of the harm spoken of above.

Even if the null is not rejected it is still possible that some or even all of the people measured had salaries in part assigned because of their race. There isn’t any way to tell looking only at the measured incomes and races. If the null is accepted, no person, it is believed, could have had their incomes caused partially by their race. Again, there isn’t any way to tell by looking only at the data. But when the null is accepted, almost all researchers will say that causality due to race is absent—replaced, impossibly, by chance. The truth is we have no idea and can have no idea, looking just at measured race and income why anybody got the salaries they did.

When the null is accepted, but the researcher had rather not accept it, perhaps because his hypothesis was consonant with his well being or it was friendly to some pre-conception, he immediately reaches to factors outside the measured data. “Well, I accepted the null, but you have to consider this was a population of new hires.” That may be the case, but since that evidence did not form part of the premises of the model, it is irrelevant if we want to judge the situation based on the output of the model. I have much more to say on this when discussing models. It is anyway obvious, that, to his credit, the researcher is looking for causes. Even if he gets them wrong, that is always the goal.

How Government Beneficence Hurts The Poor


Editor says: Note the author’s name.

The Poor in America have had less-favored status for a while. Sure, there are food stamps, low-income housing, transfer payments, and some kind of support to obtain healthcare, but the system is rigged such that once you’re in it, it will take an act of God, or tremendous internal resiliency, to overcome one’s station.

Some efforts to “help the poor” marginalize them even further. For instance, there is a push for well-to-do neighborhoods to be more welcoming to having the poor live in their midst. Like many policies, this is well intended, but simply by breathing in the same air and having the same cable TV provider and garbage pick-up doesn’t help the poor out.

What this scheme does is to make brutally clear and distinct the differences between the rich and the poor—and it may even hurt the emotional well being for the less advantaged. For instance, say that your income falls below a certain level, but through an act of government, your neighbors are much, much better off than you are. When you have to walk two miles to a bus stop, and are choking dust kicked up by your neighbor’s BMW, you can hardly count your blessings. Never mind that at the local grocery store, you have to shop at the margins—that is, your food budget will not go as far in hoity-toity land as it does at the Shop-n-Save in a neighborhood that isn’t as “desirable.”

If you are poor, and the public school is not abysmal, your child will be shoulder-to-shoulder with the indigenous populace—in this case, the privileged kids. Facts have to be faced. Rich kids can afford a lot more stuff than poor kids. Their clothes will be better and more plentiful; their after-school activities will be expensive and exotic; their home life will be full of the little luxuries that make life bearable. Poor kids have to live with the strain of not being on the same plane as their richer classmates. While it’s possible to cope, it’s hard, and it’s hard not to feed feelings of jealousy and inferiority.

The government has been working against the Poor for some time. For instance, consider the incandescent light bulb. Plentiful and cheap, which are good qualities if you’re poor. But the government had a better idea: to ban them and replace them with something that is more expensive, but yet may prove to kill us after all.

The thrift store or resale shop is a boon to the poor person. Useful things can be had at below Wal-Mart prices (or rather, this used to be the case; lately some shops are getting ahead of themselves and think they can charge $8 or more for a pair of used dungarees). One government functionary thought to herself that items for children in such shops may contain lead and forthwith, a directive was put in place mandating the testing and certification that such products are lead free. Later, a clarification (rather than a retraction) was put in place that confused the matter further. According to Snopes:

Of course, vendors of second-hand products still face the quandary that even though the CPSC has stated they are exempt from the testing and certification requirements of the CPSIA, they still have to ensure that the items they sell meet the new standards for lead and phthalate content. 

When the government gets overly concerned about regulating what goes on thrift stores—the buyer is already pretty aware of what the situation is—then precious freedom has slipped away.

And the whole idea of “healthcare” insurance is just ridiculous, and true to the cliché, the poor are hardest hit. For a young couple starting out, the bill for insurance can rival the rent. Throw in a couple of college loan payments, a car payment, and they are under water before they get out of the gate. While they may not have started as Poor, that is where they end up. All thanks to our beneficent and benevolent government.

People, regardless of income, should be able to make their own decisions about how to spend their resources, and form their own definitions of what is “desirable.” This isn’t to condemn the Poor to the ash heap, but to grant them their dignity and give them opportunity to find their way. Not everyone wants the same material things or experiences. Everyone doesn’t want to live in the same place or eat the same food or have the same job. We know that we are different from each other, and recognize that everyone has different abilities, needs, and wants.

We also know that finding one’s way—one one’s own terms—is the business of life. Many people who started life in diminished circumstances were able to improve their circumstances by hard work. Proscribed solutions by do-gooders can have unintended consequences, and one consequence may be that fewer of the Poor will be able to scale the ladder of life.

« Older posts Newer posts »

© 2017 William M. Briggs

Theme by Anders NorenUp ↑