a minipost
Some sports have doping issues and there is drug testing in many of these. There's always an issue of how good the tests are, but there's also an issue of how fair they are and how good they have to be to be fair. The best way to illustrate this is with an example.
Consider a sport with 1000 players - roughly the size of major league baseball in the US . Suppose steroid abuse is an issue and there's a test with 95% accuracy. And assume somehow it's known (or strongly suspected) that about 5% of the players are abusers. These are artificial numbers, but it's just an illustration.
What if the players are tested? We expect 50 to be abusers and 950 to be clean. The test is 95% accurate.. so 48 (rounding up from 47.5) are correctly identified. So far so good. Now consider the 950 clean players.. 5% or 48 (rounding up again) are incorrectly labeled as abusers. So of 1000 players there would be 96 positives and only a fifty-fifty chance of being right. Careers can be be ruined .. the stakes are high.
A way to sort out these conditional probabilities was described the The Reverend Thomas Bayes in the mid 1700s in a paper called Essay Towards Solving a Problem in the Doctrine of Chances. The good Reverend described the relationship between the probability an athlete is an abuser given a failed test and the probability an abuser fails the test. Consider these probabilities (apologies for notation)
P(A) = probability a drug test is positive
P(B) = probability a player is an abuser
P(A|B) = probability an abusing player tests positive
P(B|A) = probability a player has taken drugs if their test is positive
Perhaps the most important takeaway is that P(A|B) and P(B|A) are not the same! It's a very common prosecutor trick to fool the jury into thinking they are - so common that it's called the prosecutor's fallacy. But to the problem at hand.
We want to know P(B|A). We already know P(B) or at least we have the 5% estimate. So P(B) = 0.05. This also gives us P(not B) = (1 - 0.05) = 0.95 as P(B) and P(not B) must add to 1.0. We also have 47.5 (I'll go with the fractional athlete here) of 1000 drug free athletes tested positive, so P(A|not B) = 0.0475.
Bayes derived a formula showing how all of these relate. Sticking with our notation:
P(B|A) = {P(A|B) * P(B)} / {P(A/B) * P(B) + P(A|not B) * P(not B)}
= {0.95 * 0.05} / {0.95 * 0.05 + 0.0475 * 0.95}
= 0.513
This is a very unacceptable test! Although 95% accuracy sounds good on the surface, it only finds a bit better than half the abusers and incorrectly labels a lot of players. For fun try a 99% probability and a perfect 100% to see what's happening.
You can have much more complex conditionals, but this is the general idea. You really have to think things through a bit..
moonshine
"Land sakes"
A hot Sunday afternoon almost exactly fifty years ago. My sister and I were on the couch next to my Grandma King. Walter Cronkite was out connection to the small spacecraft as it slipped towards touchdown on the Sea of Tranquility. I was just a kid, but I knew this might be one of the most dramatic moments I'd witness. About then she said those two words and I had another realization.
Spacings between the generations on my mother's side were large. I never met my Grandfather - he died working as a telephone lineman for the Bell Telephone System in Utah, Idaho and Montana years before I was born. He was born a few weeks before Custer's Last Stand. Grandma was born in 1889 in the Territorial Utah theocracy. She would tell stories of the first motor car she saw, of a Butch Cassidy-like thug who ran a small business protection racket, when she read about the Wright Brothers a few years after they flew, and why moving pictures were awful (the batteries emitted a stink). They didn't have indoor plumbing until 1940, but the big event was getting electricity around 1930 .. bigger than indoor plumbing, bigger than their Ford. We couldn't get her on an airplane. Airfares from Great Falls to Salt Lake City were cheaper than riding the dog, but she heard about crashes for much of her adult life .. in fact real air safety didn't begin until the mid fifties, so she wasn't that far off.
And here she was watching glowing phosphors on a piece of glass, listening to a human voices coming from thousands of miles away along with two that had traveled by radio requiring about one and a quarter seconds to find antennas on Earth..
What happened in the next few minute was breathtaking, but I found myself wondering if her life spanned greater fundamental change than any other time in history. Would she see more fundamental change than I would? You start thinking about what fundamental means,. It still keeps me up at night.
Now there is talk about going back - sending people to the Moon and to Mars. I'm afraid I don't see it as a big deal and consider it wasteful.
Others have articulated what Apollo did for America and the world. So much was spent - nearly 4.5% of the federal budget was NASA in the mid 60s - that technologies advanced at a much more rapid pace than we'd normally see. The computer and semiconductor industries were jumpstarted. Secondary school science education changed and a large STEM pipeline to Universities was created.1 There was a morale boost for a few years, but it faded against an awful war and dramatic social change on several fronts. A moon landing, iconic as it was, faded to insignificance in a few years. The last three Apollo missions were cancelled largely because the public lost interest and politicians responded.
I'm a big proponent of space exploration and the unmanned space program has been brilliant. Putting people into space is not only expensive, but probably wrong biologically. We didn't evolve to live in such harsh environments. Most of the people who have flown in space have orbited in a region where the Earth's magnetic field shields them (and us!) from radiation. Without Earth's magnetic field it is unlikely life could have evoled on the surface or in shallow water. Anyone who stays on the Moon or Mars will have to live underground or in elaborate radiation shields. There are issues of water, air, food, human psychology, low gravity muscle and bone degradation and so on. We're the wrong tool for the job.
People, life support systems and rockets didn't scale by Moore's Law, but computation has. What a non-human kilogram in space or on another body in the Solar System can do has made leaps opening and now we have commercial businesses exploiting near Earth orbit and students orbiting satellites. We can build increasingly intelligent probes that are space faring. Plucky (I've wanted to use that word) robot explorers are getting better and better and do almost all of the meaningful exploration of the Solar System. We're really good at building and flying them as well as analyzing and wondering about what they tell us.
There are those who sayt we have to leave Earth - that it's our destiny and we've ruined the Earth. That strikes me as defeatist and driven by more by science fiction than logic and science. A failure of the imagination. Another explanation is adventure. Adventure is fine, but you can't call it real exploration at this point. My vote is for learning about the Solar System and beyond in a cost effective way as we work on repairing the damage we've done here.
We can always look up and admire the Woman in the Moon.
I would be remiss if I didn't point out that Grandma King swore in Irish Gaelic. Sadly I never learned.
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1 I've written quite a bit about the good and bad of the approach. Arguably it's created an over-supply of scientists at the cost of ignoring and even alienating the majority of students. It's sad it hasn't changed much since.
Posted at 06:52 PM in general comments, history of technology, story time | Permalink | Comments (3)
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