Category Archives: Bad Math

Wind-Powered Perpetual Motion

(NOTE: It appears that I really blew it with this one. I’m the bozo in this story. After lots of discussion, a few equations, and a bunch of time scribbling on paper, I’m convinced that I got this one wrong in a big way. No excuses; I should have done the analysis much more carefully before posting this; looking back, what I did do was pathetically shallow and, frankly, stupid. I’m sincerely sorry
for calling the guys doing the experiment bozos. I’ll follow up later this weekend with a detailed post showing my analysis, where I screwed up, and why this thing really works. In the meantime, feel free to call me an idiot in the comments; I pretty much deserve it. I’m leaving the post here, with this note, as a testament to my own stupidity and hubris in screwing this up.)

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This has been quite the day for the bad math; I’ve encountered or been sent a bunch of real mind-numbing stupidity. Unfortunately, I’m too busy with work to actually write about all of it, so as I have time, I’ll pick out the best tidbits. Today’s example is a fascinating combination of perpetual motion and wrong metrics.

Via BoingBoing comes a bunch of bozos who believe that they can create a “wind-powered” vehicle that moves faster the wind that powers it.

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If you measure the wrong thing, you get the wrong answer: Down's syndrome in Britain

One of the blogs I read regularly is Ben Goldacre’s “Bad Science”. I recommend
it highly. (Which reminds me that I really need to find some time to update my blogroll!) In saturday’s entry, he discussed a BBC Radio documentary that described how Britain is becoming a much more welcoming place for Down’s syndrome babies.

Ben did a good job of shredding it. But I also wanted to take a stab, focusing on
the mathematical problem that underlies it, because it’s a great example of two very
common errors – first, the familiar confusing correlation and causation, and
second, using incorrect metrics.

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Evolution Produces Better Antenna; Casey Luskin Very Upset

It’s always amusing to wander over to the Discovery Institute’s blogs, and see what kind of nonsense they’re spouting today. So, today, as I’m feeling like steamed crap, I took a wander over. And what did I find? High grade, low-content rubbish from my old buddy, Casey Luskin. Luskin is, supposedly, a lawyer. He’s not a scientist or a mathematician by any stretch of the imagination. There’s nothing wrong with that in the abstract; the amount of time we have to learn during our lives is finite, and no one can possible know everything. For example, I don’t know diddly-crap about law, American or otherwise; my knowledge of western history is mediocre at best; I don’t really speak any language other than english. I know some physics, but my understanding of anything beyond the basics is very limited. Even when it comes to the topic of this blog, math, I’m at best an enthusiastic amateur.

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The problem with Casey, and people like him, is that they’re ignorant of a topic where they believe that they’re experts. Growing up, I was taught to call that kind of behavior not just
ignorant, but pig-ignorant. It’s a foolish kind of arrogance, where you believe that you know as much as people who’ve spent years studying something, even though you’ve never even read an elementary textbook. It’s like the dozens of people who’ve emailed my “disproofs” of Cantor’s theorem, when they don’t actually know what “cardinality” actually means.

In this instance, Casey is annoyed because a group of people at NASA used evolutionary algorithms to create a better antenna.

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Credit Default Swaps: Gambling as Insurance

So, the financial questions keep coming. I’m avoiding a lot of them, because
(A) they bore me, and (B) I’m really not the right person to ask. I try to stay
out of this stuff unless I have some clue of what I’m talking about. Rest assured, I’m not spending all of my blogging time on this; I’ve got a post on cryptographic modes of operation in progress, which I hope to have time to finish after work this evening.

But there’s one question that keeps coming in, involving the nature of things
like so-called “Credit Default Swaps”, which I thought I’d explained, but
apparently my explanation wasn’t particularly clear. So I thought I should fill
in that gap, and strengthen the main weakness in my earlier explanations.

The basic question is: “What’s a credit default swap?”; I think what people
really want to know is both what, specifically, a credit default swap is, and how
the system surrounding credit default swaps and related monstrosities work.

Credit default swaps are interesting – in the same way that a Rube Goldberg
device is interesting. They are in a fundamental sense very simple, but the
structure that’s built up around them is so bizarre, so ridiculous on the face of
it, that when you look at it in retrospect, it’s hard to believe that anyone
actually thought that it was a good idea, or that it could ever work.

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Stupid Economic Comparisons at the New York Times

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This is just a short gripe at the NYT, and a feature
that they included in today’s Op-Ed section.

It purports to compare how the economy does under democratic versus
republican administrations. They claim that they’re computing the returns
on a 10,000 dollar stock investment under 40 years of republican
administrations and 40 years of democratic administrations, in the 80 years
since 1929.

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How Mortgages Turned into a Trillion Dollar Disaster

Ok, another batch of questions have come in, all variants on
the same theme.

The question is, if mortgages are at the root of the current economic disaster, how can it possibly result in close to a trillion dollars worth of losses?

It definitely seems strange, on two different levels. On an absolute scale, it’s hard to see how mortgage losses could add up to a trillion dollars. And on a relative scale, it’s hard to see how the foreclosures could really overwhelm the lenders when even an extremely high foreclosure rate represents a fairly modest loss considered as a percentage.

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Bad Probability and Economic Disaster; or How Ignoring Bayes Theorem Caused the Mess

There is at least a little bit of interesting bath math
to learn from in the whole financial mess going on now. A couple
of commenters beat me to it, but I’ll go ahead and write about
it anyway.

One of the big questions that comes up again and again is: how did they get away with this? How could they find any way of
taking things that were worthless, and turn them into something that could be represented as safe?

The answer is that they cheated in the math.

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Economic Disasters and Stupid Evil People

With the insanity that’s been going on in the financial world
lately, a bunch of people have asked me to post a followup to my
earlier posts on the whole mortgage disaster, to try to explain
what’s going on lately.

As I keep saying when people ask me things like this, I’m not an economist. I don’t know much about economics, and what little I do know, I tend to find terribly boring. And in this case, the discussion inevitably gets political, so I’m expecting lots of nasty email.

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Astrology and the Olympics

An alert reader sent me link to a stupid
article published by Reuters about the Olympics and Astrology.

It’s a classic kind of crackpot silliness, which I’ve described
in numerous articles before. It’s yet another example of pareidolia – that is, seeing patterns where there aren’t any.

When we look at large quantities of data, there are bound
to be things that look like patterns. In fact, it would be
surprising if there weren’t apparent parents for us to find. That’s
just the nature of large quantities of data.

In this case, it’s an astrologer claiming to have found
astrological correlations in who wins olympic competitions:

Something fishy is happening at the Olympic Games in Beijing. Put it all down to the stars.

Forget training, dedication and determination. An athlete’s star sign could be the secret to Olympic gold.

After comparing the birthdates of every Olympic winner since the modern Games began in 1896, British statistician Kenneth Mitchell discovered gold medals really are written in the stars.

He found athletes born in certain months were more likely to thrive in particular events.

Mitchell dubbed the phenomenon “The Pisces Effect” (pisces is Latin for fish) after finding that athletes born under the sign received around 30 percent more medals than any other star sign in events like swimming and water polo.

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Nonsense Pretending: Probability as a Disguise

Once again, you, my readers, have come through with some really high-grade crackpottery. This one was actually sent to me by its author, but I didn’t really look at it until several readers sent me the same link because they thought it was my kind of material. With your recommendations, I took a look, and was rewarded. In a moment of hubris, the author titled it A Possible Proof of God’s Existence from Multiverse Assumptions.

This article is basically a version of the classic big-numbers probabilistic argument for God. What makes this different is that it doesn’t line up a bunch of fake numbers and saying “Presto! Look at that great big probability: that means that it’s impossible for the universe/life/everything to exist without God!”. Instead, it takes a more scientific looking approach. It dresses the probability argument up using lots of terms and ideas from modern physics, and presents it as “If we knew the values of these variables, we could compute the probability” – with a clear bias towards the idea that the unvalued variables must have values that produced the desired result of this being a created universe.

Aside from being an indirect version of the big-numbers argument, this is also a nice example of what I call obfuscatory mathematics. See, you want to make some argument. You’re dead sure that it’s right. But it doesn’t sound convincing. So you dress it up. Don’t just assume your axioms – make up explanations for them in terms of math, so that it sounds all formal and mathy. Then your crappy assumptions will look convincing!

With that said, on to his argument!

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