# Shameful Innumeracy in the New York Times

I’ve been writing this blog for a long time – nearly four years. You’d think that
after all of the bad math I’ve written about, I must have reached the point where
I wouldn’t be surprised at the sheer innumeracy of most people – even most supposedly
educated people. But alas for me, I’m a hopeless idealist. I just never quite
manage to absorb how clueless the average person is.

Today in the New York Times, there’s an editorial which talks about
the difficulties faced by the children of immigrants. In the course of
their argument, they describe what they claim is the difference between
the academic performance of native-born versus immigrant children:

Whereas native-born children’s language skills follow a bell
curve, immigrants’ children were crowded in the lower ranks: More than
three-quarters of the sample scored below the 85th percentile in English
proficiency.

Scoring in the 85th percentile on a test means that you did better on that
test than 85 percent of the people who took it. So for the population as a
whole
, 85% of the people who took it scored below the 85th percentile –
by definition. So, if the immigrant population were perfectly matched
with the population as a whole, then you’d expect more than 3/4s the
score below the 85th percentile.

As they reported it, the most reasonable conclusion would be that on the
whole, immigrant children do better than native-born children! The
population of test takers consists of native-born children and immigrant
children. (There’s no third option – if you’re going to school here, either
you were born here, or you weren’t.) If 3/4s of immigrant children are scoring
85th percentile or below, then that means that more than 85% of
the non-immigrant children are scoring below 85th percentile.

I have no idea where they’re getting their data. Nor do I have any idea of
what they thought they were saying. But what they actually said is a
mind-boggling stupid thing, and I can’t imagine how anyone who had the most
cursory understanding of what it actually meant would miss the fact that
the statistic doesn’t in any way, shape, or form support the statement it’s
attached to.

The people who write the editorials for the New York Times don’t even
know what percentiles mean. It’s appalling. It’s worse that appalling – it’s
an absolute disgrace.

# The Chevy Volt Gets 230 mpg? Only if you use bad math.

Here’s a quick bit of obnoxious bad math. I saw this myself in a link to an AP article via Salon.com, and a reader sent me a link
to the same story via CNN. It’s yet another example of what I call a metric error: that is, the use of a measurement in a way that makes it appear to mean something very different than what it really means.

Here’s the story. Chevy is coming out with a very cool new car, the Volt. It’s
a hybrid with massive batteries. It plugs in to your household electricity when you’re home to charge its batteries. It operates as an electric car until its batteries start to get low, and then it starts running a small gas motor to power a generator. It’s a very cool idea. I’m honestly excited about cars like the volt – and Google helped develop the technology behind it, which biases me even more in its favor. So you’d expect me to be very supportive of the hype around it, right? I wish I could. But GM has decided that the best way to promote it is to use bad math to tell lies to make it look even better than it really is.

Chevy has announced that for city driving, the Volt will get gas mileage of 230 miles per gallon.

That’s nonsense. Pure, utter rubbish.

# Bill O'Reilly on Life Expectancy: Dumbest Man on Earth?

An alert reader just sent me, via “Media Matters”, the single dumbest real-life
video clip that I have ever seen. In case you’ve been living under a rock, Bill O’Reilly is
a conservative radio and TV talk-show host. He’s known for doing a lot of really obnoxious
things, ranging from sexually harassing at least one female employee, to sending some of
his employees to stalk people who he doesn’t like, to shutting off the microphones of
guests on his show if he’s losing an argument. In short, he’s a loudmouthed asshole who
gets off on bullying people.

But that’s just background. As a conservative commentator, he’s been going off on
the evils of Obama’s supposedly socialist healthcare reform. That’s frequently
taken the form of talking about how horrible medical care is under Canada’s
the insanity follows.

The question came from a viewer named Peter from Victoria, BC, who asked: “Has anyone noticed
that life expectancy in Canada under our health system is higher than the USA?”

Bill’s response:” Well, that’s to be expected Peter, because we have 10 times
as many people as you do. That translates to 10 times as many accidents,
crimes, down the line.” Delivered, of course, in BillO’s trademark patronizing
style.

# More Deceptive Graphs: Scales Matter

Yet More Deceptive Graphs

As you’ve probably heard, there was a horrible incident in Pittsburgh this weekend, in
which a crazed white supremacist who believed that Obama was coming to take his guns shot and
killed three policemen. Markos Moulitsas, of Daily Kos, pointed out lunatics like this shooter
are acting on conspiracy theories that are being relentlessly promoted by the likes of Glen
Beck and Michelle Bachman. It’s not an unreasonable thing to point out, given the amount of
time that Beck and Bachman have spent lately talking about the impending socialist/fascist
crackdowns that will require a revolutionary response from all right-thinking patriotic
citizens.

Now, you may think that Kos is an idiot. In fact, even though we agree on many
political issues, I think that Kos is an idiot. I (obviously from what
I wrote above) happen to agree with the basic hypothesis that if you tell
people that the government is going to come and get that and that they need to
defend themselves, that some people are going to believe that the government is
coming to get them and that they need to defend themselves. But the way
that Kos responded was disgusting; it was latching on to a tragic event in
a shallow, snide, heartless way.

But whether you think Kos is an ass ore not isn’t the point. Regardless of your opinion of
the man, there’s no arguing the fact that he’s created a website that draws a really
astonishing amount of traffic, and has become a nexus for many activists on the political
left.

And that, in turn, naturally draws hatred and mockery from the political right. Because,
you see, no one who disagrees with those fine patriotic folks could possibly be an
honest, serious person. They must be a bunch of scheming bastards, obviously.

So, when Kos came out bitching about how the rantings of various crazies really do
have a connection to the actions of people like the Pittsburgh killer, naturally it couldn’t be that he actually believed that people ranting about how the President is
creating a fascistic tyranny that’s going to come take all of your guns could actually
inspire a crazy person to believe that the President creating a fascistic tyranny that was going to come and take away his guns. No, that couldn’t be. He must be up to something – like trawling for hits!

Which, finally, brings us to our topic.

A conservative blogger named Moe Lane posted his theory about why Kos spoke out about the Pittsburgh shooter. It’s because his pageviews have declined so much. But, of course, it wouldn’t be good enough to just say that DKos pageviews are down – he’s got to show that it’s specific to those dirty liberals. So he produces two graphs – one for DKos, and one for RedState, a major conservative site. Here are his graphs; DKos first, Redstate second:

A quick glance shows that both had a huge spike right around the elections, and then they
dropped off pretty dramatically. Then both had a slow upward trend. But the RedState trend
looks a lot steeper.

# Financial Morons, and Quadratics vs. Linears

I wasn’t going to write about this, because I really don’t have much to add. But people keep mailing it to me, so in order to shut you all up, I’ll chip in.

As everyone knows by now, we’re in the midst of a really horrible
financial disaster. I’ve argued in the past on this blog that the root cause of the entire disaster is pure, simple stupidity on the part of people in the financial business. People gave out mortgages that any
sane rational person would have considered ridiculous. And then they built huge, elaborate financial structures on top of those mortgages, pretending that by somehow piling layer upon layer, loan upon loan, that
they were somehow creating something that could be considered real wealth.

They gave themselves bonuses that boggled the mind. Even after the whole ridiculous system came tumbling down, they continue to give themselves ridiculous bonuses. Insane bonuses. They’ve been writing themselves checks for millions of dollars to continue to operate their
businesses – even after taking billions of dollars in loans from the government to prevent them from going out of business. I consider
this to be downright criminal. But even if it’s not criminal, it’s
incredibly stupid. The very people who ran those firms right to the edge of bankruptcy, who nearly took down our entire financial system
are being rewarded. Not only are they being allowed to continue
to rut the businesses that they pretty much destroyed, but they’ve
been paying themselves an astonishing amount of money to do it. And now they’re complaining bitterly about the fact that the government
wants to limit them to a paltry half-million dollars of salary per year.

They argue that they must be allowed to earn more than that. Because after all, the people who run those businesses are special. They’re “the best and the brightest”. They’re
extra-smart. No one else could possibly run those businesses. We can’t rely on anyone who’d accept a puny half-mil – they won’t be smart enough. They don’t have the special knowledge of the business that these people do.

There’s one minor problem with that argument: it doesn’t work. A couple of weeks ago, some idiot at JP Morgan circulated a chart that was supposed to summarize just how bad the financial disaster has been. The chart circulated for a couple of weeks – bounced from mailbox to mailbox, sent from one financial genius to another.

Only the chart was blatantly, obviously, trivially wrong, and anyone who had the slightest damned clue of the assets those businesses managed – i.e., the kind of thing that the idiot who drew the chart was supposed to know – should have been able to tell at a glance how wrong it was. But they didn’t. In fact, the damned thing didn’t stop circulating until (of all people) Bob Cringely
flamed it. Go look at the chart – it’s up at the top of this post.

# Metric Abuse – aka Lying with Statistics

I’m behind the curve a bit here, but I’ve seen and heard a bunch of
people making really sleazy arguments about the current financial stimulus
package working its way through congress, and those arguments are a perfect
example of one of the classic ways of abusing statistics. I keep mentioning metric errors – this is another kind of metric error. The difference between this and some of the other examples that I’ve shown is that this is deliberately dishonest – that is, instead of accidentally using the wrong metric to get a wrong answer, in this case, we’ve got someone deliberately taking one metric, and pretending that it’s an entirely different metric in order to produce a desired result.

As I said, this case involves the current financial stimulus package that’s working its way through congress. I want to put politics aside here: when it comes to things like this financial stimulus, there’s plenty of room for disagreement.
Economic crises like the one we’re dealing with right now are really uncharted territory – they’re very rare, and the ones that we have records of have each had enough unique properties that we don’t have a very good collection of evidence
to use to draw solid conclusions about recoveries from them work. This isn’t like
physics, where we tend to have tons and tons of data from repeatable experiments; we’re looking at a realm where there are a lot of reasonable theories, and there isn’t enough evidence to say, conclusively, which (if any) of them is correct. There are multiple good-faith arguments that propose vastly different ways of trying
to dig us out of this disastrous hole that we’re currently stuck in.

Of course, it’s also possible to argue in bad faith, by
creating phony arguments. And that’s the subject of this post: a bad-faith
argument that presents real statistics in misleading ways.

# Selective Data and Global Warming

One of the most common sleazy tricks used by various sorts of denialists
comes back to statistics – invalid and deceptive sampling methods. In fact,
the very first real post on the original version of this blog was a shredding of
a paper by Mark and David Geier that did this.

Proper statistical analysis relies on a kind of blindness. Many of the things
that you look for, you need to look for in a way that doesn’t rely on any a priori
knowledge of the data. If you look at the data, and find what appears to be an
interesting property of it, you have to be very careful to show that it’s
a real phenomena – and you do that by performing blind analyses that demonstrate
its reality.

The reason that I bring this up is because one of my fellow SBers,
Tim Lambert, posted something about a particularly sleazy example of this
by Michael Duffy, a global warming denialist over at his blog, Deltoid.

The situation is that there’s a Duffy claims
that global warming stopped in 2002. It didn’t. But he makes it look like it did by using a deliberately dishonest way of sampling the data.

Yet another reader sent me a link to a really annoying article at a site called “Daily Tech”. The article has been more than adequately debunked by Darksyde at Daily Kos, but it’s a very typical example of a general kind of argument made both for and against global warming, which I find extremely annoying.

The basic argument takes one of two forms:

1. Wow, look how hot it is today! How can anyone possible deny global
warming?
2. Wow, look how cold it is today! How can those idiots believe in global
warming?

These are both examples of confusing weather with climate. That confusion is a typical example of a common statistical error:
using aggregate data to draw conclusions about specific individuals, or using a single individual to draw conclusions about an aggregate. Individual data points and aggregates are very different things, and you can’t just arbitrarily go from one to another.

# Washington State and GOP Vote Counting Fraud?

I’ve been getting a lot of mail from people asking for my take on
the news about the Washington GOP primary. Most have wanted me to
debunk rumours about vote fixing there, the way that I tried to debunk the