Science

The end of hard-edged science?

Posted on by John

Bradley Efron says that science is moving away from things like predicting sunrise times and toward predicting things like the weather. The trend is away from studying precisely predictable systems, what Efron calls “hard-edged science,” and toward studying systems “where predictability is tempered by a heavy dose of randomness.”

Hard-edged science still dominates public perceptions, but the attention of modern scientists has swung heavily toward rainfall-like subjects, the kind where random behavior plays a major role. … Deterministic Newtonian science is majestic, and the basis of modern science too, but a few hundred years of it pretty much exhausted nature’s storehouse of precisely predictable events. Subjects like biology, medicine, and economics require a more flexible scientific world view, the kind we statisticians are trained to understand.

Certainly there is increased interest in systems containing “a heavy dose of randomness” but can we really say that we have “pretty much exhausted nature’s storehouse of precisely predictable effects”?

Source: Modern Science and the Bayesian-Frequentist Controversy

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Final velocity

Posted on by John

My daughter and I were going over science homework this evening. A ball falls for 10 seconds. What is its final velocity?

JC: So how fast is the ball going when it hits the ground?

RC: Zero. It stops before it bounces back up.

JC: Well, how fast is it going just before it hits the ground?

RC: They didn’t ask the almost final velocity. They asked for the final velocity.

Acupuncture and confirmation bias

Posted on by John

Here’s another excerpt from The decline effect and the scientific method that I wrote about a couple weeks ago.

Between 1966 and 1995, there were forty-seven studies of acupuncture in China, Taiwan, and Japan, and every single trial concluded that acupuncture was an effective treatment. During the same period, there were ninety-four clinical trials of acupuncture in the United States, Sweden, and the U.K., and only fifty-six per cent of these studies found any therapeutic benefits.

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Scientific results fading over time

Posted on by John

A recent article in The New Yorker gives numerous examples of scientific results fading over time. Effects that were large when first measured become smaller in subsequent studies. Firmly established facts become doubtful. It’s as if scientific laws are being gradually repealed. This phenomena is known as “the decline effect.” The full title of the article is The decline effect and the scientific method.

The article brings together many topics that have been discussed here: regression to the mean, publication bias, scientific fashion, etc. Here’s a little sample.

“… when I submitted these null results I had difficulty getting them published. The journals only wanted confirming data. It was too exciting an idea to disprove, at least back then.” … After a new paradigm is proposed, the peer-review process is tilted toward positive results. But then, after a few years, the academic incentives shift—the paradigm has become entrenched—so that the most notable results are now those that disprove the theory.

This excerpt happens to be talking about “fluctuating asymmetry,” the idea that animals prefer more symmetric mates because symmetry is a proxy for good genes. (I edited out references to fluctuating asymmetry from the quote to emphasize that the remarks could equally apply to any number of topics. ) Fluctuating asymmetry was initially confirmed by numerous studies, but then the tide shifted and more studies failed to find the effect.

When such a shift happens, it would be reassuring to believe that the initial studies were simply wrong and that the new studies are right. But both the positive and negative results confirmed the prevailing view at the time they were published. There’s no reason to believe the latter studies are necessarily more reliable.

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Occam’s razor and Bayes’ theorem

Posted on by John

Occam’s razor says that if two models fit equally well, the simpler model is likely to be a better description of reality. Why should that be?

A paper by Jim Berger suggests a Bayesian justification of Occam’s razor: simpler hypotheses have higher posterior probabilities when they fit well.

A simple model makes sharper predictions than a more complex model. For example, consider fitting a linear model and a cubic model. The cubic model is more general and fits more data. The linear model is more restrictive and hence easier to falsify. But when the linear and cubic models both fit, Bayes’ theorem “rewards” the linear model for making a bolder prediction. See Berger’s paper for a details and examples.

From the conclusion of the paper:

Ockham’s razor, far from being merely an ad hoc principle, can under many practical situations in science be justified as a consequence of Bayesian inference. Bayesian analysis can shed new light on what the notion of “simplest” hypothesis consistent with the data actually means.

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The solar system in a glass of wine

Posted on by John

William Blake’s poem Auguries of Innocence opens with these famous lines:

To see a world in a grain of sand,
And a heaven in a wild flower,
Hold infinity in the palm of your hand,
And eternity in an hour.

This poem came to mind when I saw @mathematicsprof post the following on Twitter:

At your next holiday party, look straight down into your glass of wine and tilt the glass one degree. You will see the elliptic orbit of the earth.

If you tilt your glass 12 degrees you’ll see the orbit of Mercury. In general, if you tilt your glass θ degrees you’ll see an ellipse with eccentricity sin(θ).

(I’ve taken the liberty of editing the original tweets to take advantage of the extra breathing room outside of Twitter. Original tweets here and here.)

I like this for two reasons: it’s a great astronomy illustration, and it’s an example of how much information you can get into two 140-character messages.

Scientific opposition to the war on cancer

Posted on by John

On December 9, 1969 the Washington Post ran a full-page ad that began

Mr. Nixon: You can cure cancer.

If America could put a man on the moon, she should be able to cure cancer. And why not? Well, because cancer research isn’t rocket science. (Actually, rocket science isn’t science; it’s engineering.) The science necessary to put a man on the moon was well known; the science necessary to cure cancer was not.

President Nixon was eager to comply with the request for massive funding for cancer research. However, many scientists were opposed to the idea. Cancer researcher Sol Spiegelman, for example, believed such a push was premature.

An all-out effort at this time would be like trying to land a man on the moon without knowing Newton’s laws of gravity.

James Watson warned

… we must reject the notion that we will be lucky. … Instead we will be witnessing a massive expansion of well-intentioned mediocrity.

How many scientists today would argue against a funding increase for their area of study?

Quotes taken from Emperor of all Maladies

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Rice/NASA land deal

Posted on by John

Rice University donated the land for NASA’s Johnson Space Center. However, there were strings attached. According to Rocket Men,

If NASA gives up manned space flight, however, under the terms of its lease , it will have to relinquish Houston’s Johnson Spacecraft [sic] Center back to Rice University.

I imagine NASA will always at least talk about putting people in space so they can hold on to their land.

Update: Here’s a newspaper clipping about the deal. I don’t know where it’s from or whether it’s accurate.

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After two days, I’d turned into an idiot

Posted on by John

Ever wonder why astronauts schedules are crammed with activity? A simple explanation is that time in space is a very limited commodity and so they naturally want to accomplish as much as possible. While that’s undoubtedly true, there’s also another reason.

Early in the space program, a NASA psychiatrist spent two days in an isolation tank with scuba gear to experience simulated weightlessness.

I thought a little, and then I stopped thinking altogether. … incredible how idleness of body leads to idleness of mind. After two days, I’d turned into an idiot. That’s the reason why, during a flight, astronauts are always kept busy.

From Rocket Men.

Related post: Not exactly rocket science