Category Archives: Science and Edumacation

Mathematical Malpractice Watch: Hurricanes

There’s a new paper out that claims that hurricanes with female names tend to be deadlier than ones with male names based on hurricane data going back to 1950. They attribute this to gender bias, the idea that people don’t take hurricanes with female-names seriously.

No, this is not the onion.

I immediately suspected a bias. For one thing, even with their database, we’re talking about 92 events, many of which killed zero people. More important, all hurricanes had female names until 1979. What else was true before 1979? We had a lot less advanced warning of hurricanes. In fact, if you look up the deadliest hurricanes in history, they are all either from times before we named them or when hurricanes all had female names. In other words, they may just be measuring the decline in hurricane deadliness.

Now it’s possible that the authors use some sophisticated model that also account for hurricane strength. If so, that might mitigate my analysis. But I’m dubious. I downloaded their spreadsheet, which is available for the journal website. Here is what I found:

Hurricanes before 1979 averaged 27 people killed.

Hurricanes since 1979 average 16 people killed.

Hurricanes since 1979 with male names average … 16 people killed.

Hurricanes since 1979 with female names averaged … 16 people killed.

Maybe I’m missing something. How did this get past a referee?

Update: Ed Yong raises similar points here. The authors say that cutting the sample at 1979 made the numbers too small and so therefore use an index of how feminine or masculine the names were. I find that dubious when a plain and simple average will give you an answer. Moreover, they try this qualifier in the comments:

What’s more, looking only at severe hurricanes that hit in 1979 and afterwards (those above $1.65B median damage), 16 male-named hurricane each caused 23 deaths on average whereas 14 female-named hurricanes each caused 29 deaths on average. This is looking at male/female as a simple binary category in the years since the names started alternating. So even in that shorter time window since 1979, severe female-named storms killed more people than did severe male-named storms.

You be the judge. I average 54 post-1978 storms totally 1200 deaths and get even numbers. They narrow it to 30 totally 800 deaths and claim a bias based on 84 excess deaths. That really crosses as stretching to make a point.

Update: My friend Peter Yoachim did a K-S test of the data and found a 97% chance that the male- and female-named hurricanes were drawn from the same distribution. This is a standard test of the null hypothesis and wasn’t done at all. Ridiculous.

Absolutely Nothing Happened in Sector 83 by 9 by 12 Today

Last night, the science social media sphere exploded with the news of a potential … something … in our nearest cosmic neighbor, M31. The Swift mission, which I am privileged to work for, reported the discovery of a potential bright X-ray transient in M31, a sign of a high-energy event. For a while, we had very little to go on — Goddard had an unfortunately timed power outage. Some thought (and some blogs actually reported) that we’d seen a truly extraordinary event — perhaps even a nearby gamma-ray burst. But it turned out to be something more mundane. My friend and colleague Phil Evans has a great explanation:

It started with the Burst Alert Telescope, or BAT, on board Swift. This is designed to look for GRBs, but will ‘trigger’ on any burst of high-energy radiation that comes from an area of the sky not known to emit such rays. But working out if you’ve had such a burst is not straightforward, because of noise in the detector, background radiation etc. So Swift normally only triggers if it’s really sure the burst of radiation is real; for the statisticians among you, we have a 6.5-σ threshold. Even then, we occasionally get false alarms. But we also have a program to try to spot faint GRBs in nearby galaxies. For this we accept lower significance triggers from BAT if they are near a known, nearby galaxy. But these lower significance triggers are much more likely to be spurious. Normally, we can tell that they are spurious because GRBs (almost always) have a glow of X-rays detectable for some time after the initial burst, an ‘afterglow’. The spurious triggers don’t have this, of course.

In this case, it was a bit more complicated There was an X-ray source consistent with the BAT position. The image to the right shows the early X-ray data. The yellow circle shows the BAT error box – that is, the BAT told us it thought it had seen something in that circle. The orange box shows what the XRT could see at the time, and they grey dots are detected X-rays. The little red circle marks where the X-ray source is.

Just because the X-ray object was already known about, and was not something likely to go GRB doesn’t mean it’s boring. If the X-ray object was much brighter than normal, then it is almost certainly what triggered the BAT and is scientifically interesting. Any energetic outburst near to Earth is well worth studying. Normally when the Swift X-ray telescope observes a new source, we get various limited data products sent straight to Earth, and normally some software (written by me!) analyses those data. In this case, there was a problem analysing those data products, specifically the product from which we normally estimate the brightness. So the scientists who were online at the time were forced to use rougher data, and from those it looked like the X-ray object was much brighter than normal. And so, of course, that was announced.

The event occurred at about 6:15 EDT last night. I was feeding kids and putting them to bed but got to work on it after a couple of hours. At about 9:30, my wife asked what I was up to and I told her about a potential event in M31, but was cautious. I said something like: “This might be nothing; but if it is real, it would be huge.” I wish I could say I had some prescience about what the later analysis would show, but this was more my natural pessimism. That skeptical part of my mind kept going on about how unlikely a truly amazing event was (see here).

My role would turn out to be a small one. It turned out that Swift had observed the region before. And while Goddard and its HEASARC data archive were down, friend and fellow UVOT team member Caryl Gronwall reminded me that the MAST archive was not. We had not observed the suspect region of M31 in the same filters that Swift uses for its initial observations. But we knew there was a globular cluster near the position of the even and, by coincidence, I had just finished a proposal on M31’s globular clusters. I could see that the archival measures and the new measure were consistent with a typical globular cluster. Then we got a report from the GTC. Their spectrum only showed the globular cluster.

This didn’t disprove the idea of a transient, of course. Many X-ray transients don’t show a signature in the optical and it might not have been the globular cluster anyway. But it did rule out some of the more exotic explanations. Then the other shoe dropped this morning when the XRT team raced to their computers, probably still in their bathrobes. Their more detailed analysis showed that the bright X-ray source was a known source and had not brightened. So … no gamma-ray burst. No explosive event.

Phil again:

I imagine that, from the outside, this looks rather chaotic and disorganised. And the fact that this got publicity across the web and Twitter certainly adds to that! But in fact this highlights the challenges facing professional astronomers. Transient events are, by their nature, well, transient. Some are long lived, but others not. Indeed, this is why Swift exists, to enable us to respond very quickly to the detection of a GRB and gather X-ray, UV and optical data within minutes of the trigger. And Swift is programmed to send what it can of that data straight to the ground (limited bandwidth stops us from sending everything), and to alert the people on duty immediately. The whole reason for this is to allow us to quickly make some statements about the object in question so people can decide whether to observe it with other facilities. This ability has led to many fascinating discoveries, such as the fact that short GRBs are caused by two neutron stars merging, the detection of a supernova shock breaking out of a star and the most distant star even seen by humans, to name just 3. But it’s tough. We have limited data, limited time and need to say something quick, while the object is still bright. People with access to large telescopes need to make a rapid decision, do they sink some of their limited observing time into this object? This is the challenge that we, as time-domain astronomers, face on a daily basis. Most of this is normally hidden from the world at large because of course we only publish and announce the final results from the cases where the correct decisions were made. In this case, thanks to the power of social media, one of those cases where what proved to be the wrong decision has been brought into the public eye. You’ve been given a brief insight into the decisions and challenges we have to face daily. So while it’s a bit embarrassing to have to show you one of the times where we got it wrong, it’s also good to show you the reality of science. For every exciting news-worthy discovery, there’s a lot of hard graft, effort, false alarms, mistakes, excitement and disappointment. It’s what we live off. It’s science.

Bingo.

People sometimes ask me why I get so passionate about issues like global warming or vaccination or evolution. While the political aspects of these issues are debatable, I get aggravated when people slag the science, especially when it is laced with dark implications of “follow the money” or claims that scientists are putting out “theories” without supporting evidence. Skeptics claims, for example, that scientists only support global warming theory or vaccinations because they would not get grant money for claiming otherwise.

It is true: scientists like to get paid, just like everyone else. We don’t do this for free (mostly). But money won’t drag you out of bed at 4 in the morning to discover a monster gamma-ray burst. Money doesn’t keep you up until the wee hours pounding on a keyboard to figure out what you’ve just seen. Money didn’t bounce my Leicester colleagues out of bed at the crack of dawn to figure out what we were seeing. Money doesn’t sustain you through the years of grad school and the many years of soft-money itinerancy. Hell, most scientists could make more money if they left science. One of the best comments I ever read on this was on an old slash-dot forum: “Doing science for the money is like having sex for the exercise.”

What really motivates scientists is the answer. What really motivates them is finding out something that wasn’t known before. I have been fortunate in my life to have experienced that joy of discovery a few times. There have been moments when I realized that I was literally the only person on Earth to know something, even if that something was comparatively trivial, like the properties of a new dwarf galaxy. That’s the thrill. And despite last night’s excitement being in vain, it was still thrilling to hope that we’d seen something amazing. And hell, finding out it was not an amazing event was still thrilling. It’s amazing to watch the corrective mechanisms of the scientific method in action, especially over the time span of a few hours.

Last night, science was asked a question: did something strange happen in M31? By this morning, we had the answer: no. That’s not a bad day for science. That’s a great one.

One final thought: one day, something amazing is going to happen in the Local Universe. Some star will explode, some neutron stars will collide or something we haven’t even imagined will happen. It is inevitable. The question is not whether it will happen. The question is: will we still be looking?

Low Class Cleavage

It’s the end of the month, so time to put up a few posts I’ve been tinkering with.

No, just give the Great Unwashed a pair of oversized breasts and a happy ending, and they’ll oink for more every time.

– Charles Montgomery Burns

A few months ago, this study was brought to my attention:

It has been suggested human female breast size may act as signal of fat reserves, which in turn indicates access to resources. Based on this perspective, two studies were conducted to test the hypothesis that men experiencing relative resource insecurity should perceive larger breast size as more physically attractive than men experiencing resource security. In Study 1, 266 men from three sites in Malaysia varying in relative socioeconomic status (high to low) rated a series of animated figures varying in breast size for physical attractiveness. Results showed that men from the low socioeconomic context rated larger breasts as more attractive than did men from the medium socioeconomic context, who in turn perceived larger breasts as attractive than men from a high socioeconomic context. Study 2 compared the breast size judgements of 66 hungry versus 58 satiated men within the same environmental context in Britain. Results showed that hungry men rated larger breasts as significantly more attractive than satiated men. Taken together, these studies provide evidence that resource security impacts upon men’s attractiveness ratings based on women’s breast size.

Sigh. It seems I am condemned to writing endlessly about mammary glands. I don’t have an objection to the subject but I do wish someone else would approach these “studies” with any degree of skepticism.

This is yet another iteration of the breast size study I lambasted last year and it runs into the same problems: the use of CG figures instead of real women, the underlying inbuilt assumptions and, most importantly, ignoring the role that social convention plays in this kind of analysis. To put it simply: men may feel a social pressure to choose less busty CG images, a point I’ll get to in a moment. I don’t see that this study sheds any new light on the subject. Men of low socioeconomic status might still feel less pressure to conform to social expectations, something this study does not seem to address at all. Like most studies of human sexuality, it makes the fundamental mistake of assuming that what people say is necessary reflective of what they think or do and not what is expected of them.

The authors think that men’s preference for bustier women when they are hungry supports their thesis that the breast fetish is connected to feeding young (even though is zero evidence that large breasts nurse better than small ones). I actually think their result has no bearing on their assumption. Why would hungrier men want fatter women? Because they want to eat them? To nurse off them? I can think of good reasons why hungry men would feel less bound by social convention, invest a little less thought in a silly social experiment and just press the button for the biggest boobs. I think that hungry men are more likely to give you an honest opinion and not care that preferring the bustier woman is frowned upon. Hunger is known to significantly alter people’s behavior in many subtle ways but these authors narrow it to one dimension, a dimension that may not even exist.

And why not run a parallel test on women? If bigger breasts somehow provoke a primal hunger response, might that preference be built into anyone who nursed in the first few years of life?

No, this is another garbage study that amounts to saying that “low-class” men like big boobs while “high-class” men are more immune to the lure of the decolletage and so … something. I don’t find that to be useful or insightful or meaningful. I find that it simply reinforces an existing preconception.

There is a cultural bias in some of the upper echelons of society against large breasts and men’s attraction to them. That may sound crazy in a society that made Pamela Anderson a star. But large breasts and the breast fetish are often seen, by elites, as a “low class” thing. Busty women in high-end professions sometimes have problems being taken seriously. Many busty women, including my wife, wear minimizer bras so they’ll be taken more seriously (or look less matronly). I’ve noticed that in the teen shows my daughter sometimes watches, girls with curves are either ditzy or femme fatales. In adult comedies, busty women are frequently portrayed as ditzy airheads. Men who are attracted to buxom women are often depicted as low-class, unintelligent and uneducated. Think Al Bundy.

This is, of course, a subset of a mentality that sees physical attraction itself as a low-class animalistic thing. Being attracted to a woman because she’s a Ph.D. is obviously more cultured, sophisticated and enlightened than being attracted to a woman because she’s a DD. I don’t think attraction is monopolar like that. As I noted before, a man’s attraction to a woman is affected by many factors — her personality, her intelligence, her looks. Breast size is just one slider on the circuit board that it is men’s sexuality and probably not even the most important. But it’s absurd to pretend the slider doesn’t exist or that it is somehow less legitimate than the others. We are animals, whatever our pretensions.

Last year, a story exploded on the blogosphere about a naive physics professor who was duped into becoming a drug mule by the promise that he would marry Denise Milani, an extremely buxom non-nude model. What stunned me in reading about the story was the complete lack of any sympathy for him. Granted, he is an arrogant man who isn’t particularly sympathetic. But a huge amount of abuse was heaped on him, much of it focusing on his fascination with a model and particularly a model with extremely large and likely artificial breasts. The tone was that there must be something idiotic and crude about the man to fall for such a ruse and for such a woman.

The reaction to the story not only illuminated a cultural bias but how that bias can become particularly potent when the breasts in question are implants. The expression “big fake boobs” is a pejorative that men and women love to hurl at women they consider low class or inferior. Take Jenny McCarthy. There are very good reasons to criticize McCarthy for her advocacy of anti-vaccine hysteria (although I think the McCarthy criticism is a bit overblown since most people are getting this information elsewhere and McCarthy wasn’t the one who committed research fraud). But no discussion of McCarthy is complete until someone has insulted her for having implants and the existence of those implants has been touted as a sign of her obvious stupidity and the stupidity of those who follow her.

McCarthy actually doesn’t cross me as that stupid; she crosses me as badly misinformed. And it’s not like there aren’t hordes of very smart people who haven’t bought into the anti-vaccine nonsense even sans McCarthy. But putting that aside, I don’t know what McCarthy’s breasts have to do with anything. Do people honestly think it would make a difference is she was an A-cup?

To return to this study and the one I lambasted last year: what I see is not only bad science but a subtle attempt by science to reinforce the stereotype that large breasts and an attraction to them are animalistic, low-class and uneducated. Bullshit speculation claims that men’s attraction to breasts is some primitive instinct. And more bullshit research claims that wealthy educated men can resist this primitive instinct but poorer less-educated men wallow in their animalistic desires. And when these garbage studies come out, blogs are all too eager to hype them, saying, “See! We told you those guys who liked big boobs were ignorant brutes!”

I think this is just garbage. The most “enlightened” academic is just as likely to ogle a busty woman when she walks by. He might be better trained at not being a jerk about it because he walks in social circles where wolf-whistles and come-ons are unacceptable. And he lives in a society where, if a bunch of social scientists are leering over you, you pretend to like the less busty woman. But all men live secret erotic lives in their heads. It’s extremely difficult to tease that information out and certainly not possible with an experiment as crude and obvious as this.

Once again, we see the biggest failing in sex research: asking people what they want instead of getting some objective measure. There are better approaches, some of which I mentioned in my previous article. If I were to approach this topic, I would look at the google search database used in A Billion Wicked Thoughts to see if areas of high education (e.g., college towns) were less likely to look at porn in general and porn involving busty women in particular. That might give you some useful information. But there’s a danger that it wouldn’t enforce the bias we’ve built up against big breasts and the men who love them.

Mathematical Malpractice Watch: A Trilogy of Error

Three rather ugly instances of mathematical malpractice have caught my attention in the last month. Let’s check them out.

The Death of Facebook or How to Have Fun With Out of Sample Data

Last month, Princeton researchers came out with the rather spectacular claim that the social network Facebook would be basically dead within a few years. The quick version is that they fit an epidemiological model to the rise and fall of MySpace. They then used that same model, varying the parameters, to fit Google trends on searches for Facebook. They concluded that Facebook would lose 80% of its customers by 2017.

This was obviously nonsese as detailed here and here. It suffered from many flaws, notably assuming that the rise and fall of MySpace was necessarily a model for all social networks and the dubious method of using Google searches instead of publicly available traffic data as their metric.

But there was a deeper flaw. The authors fit a model of a sharp rise and fall. They then proclaim that this model works because Facebook’s google data follows the first half of that trend and a little bit of the second. But while the decline in Facebook Google searches is consistent with their model, it is also consistent with hundreds of others. It would be perfectly consistent with a model that predicts a sharp rise and then a leveling off as the social network saturates. Their data are consistent with but not discriminating against just about any model.

The critical part of the data — the predicted sharp fall in Facebook traffic — is out of sample (meaning it hasn’t happened yet). But based on a tiny sliver of data, they have drawn a gigantic conclusion. It’s Mark Twain and the length of the Mississippi River all over again.

We see this a lot in science, unfortunately. Global warming models often predict very sharp rises in temperature — out of sample. Models of the stock market predict crashes or runs — out of sample. Sports twerps put together models that predict Derek Jeter will get 4000 hits — out of sample.

Anyone who does data fitting for a living knows this danger. The other day, I fit a light curve to a variable star. Because of an odd intersection of Fourier parameters, the model predicted a huge rise in brightness in the middle of its decay phase because there were no data to constrain it there. So it fit a small uptick in the decay phase as though it were the small beginning of a massive re-brightening.

The more complicated the model, the more danger there is of drawing massive conclusions from tiny amounts of data or small trends. If the model is anything other than a straight line, be very very wary at out-of-sample predictions, especially when they are predicting order-of-magnitude changes.

A Rape Epidemic or How to Reframe Data:

The CDC recently released a study that claimed that 1.3 million women were raped and 12.6 million more were subject to sexual violence in 2010. This is six or more times the estimates of the FBI’s extremely rigorous NCVS estimate. Christina Hoff Summers has a breakdown of why the number is so massive:

It found them by defining sexual violence in impossibly elastic ways and then letting the surveyors, rather than subjects, determine what counted as an assault. Consider: In a telephone survey with a 30 percent response rate, interviewers did not ask participants whether they had been raped. Instead of such straightforward questions, the CDC researchers described a series of sexual encounters and then they determined whether the responses indicated sexual violation. A sample of 9,086 women was asked, for example, “When you were drunk, high, drugged, or passed out and unable to consent, how many people ever had vaginal sex with you?” A majority of the 1.3 million women (61.5 percent) the CDC projected as rape victims in 2010 experienced this sort of “alcohol or drug facilitated penetration.”

What does that mean? If a woman was unconscious or severely incapacitated, everyone would call it rape. But what about sex while inebriated? Few people would say that intoxicated sex alone constitutes rape — indeed, a nontrivial percentage of all customary sexual intercourse, including marital intercourse, probably falls under that definition (and is therefore criminal according to the CDC).

Other survey questions were equally ambiguous. Participants were asked if they had ever had sex because someone pressured them by “telling you lies, making promises about the future they knew were untrue?” All affirmative answers were counted as “sexual violence.” Anyone who consented to sex because a suitor wore her or him down by “repeatedly asking” or “showing they were unhappy” was similarly classified as a victim of violence. The CDC effectively set a stage where each step of physical intimacy required a notarized testament of sober consent.

In short, they did what is called “reframing”. They took someone’s experiences, threw away that person’s definition of them and substituted their own definition.

This isn’t the first time this has happened with rape stats nor the first time Summers had uncovered this sort of reframing. Here is an account of how researchers decided that women who didn’t think they had been raped were, in fact, raped, so they could claim a victimization rate of one in four.

Scientists have to classify things all the time based on a variety of criteria. The universe is a messy continuum; to understand it, we have to sort things into boxes. I classify stars for a living based on certain characteristics. The problem with doing that here is that women are not inanimate objects. Nor are they lab animals. They can have opinions of their own about what happened to them.

I understand that some victims may reframe their experiences to try to lessen the trauma of what happened to them. I understand that a woman can be raped but convince herself it was a misunderstanding or that it was somehow her fault. But to a priori reframe any woman’s experience is to treat them like lab rats, not human beings capable of making judgements of their own.

But it also illustrates a mathematical malpractice problem: changing definitions. This is how 10,000 underage prostitutes in the United States becomes 200,000 girls “at risk”. This is how small changes in drug use stats become an “epidemic”. If you dig deep into the studies, you will find the truth. But the banner headline — the one the media talk about — is hopelessly and deliberately muddled.

Sometimes you have to change definitions. The FBI changed their NCVS methodology a few years ago on rape statistics and saw a significant increase in their estimates. But it’s one thing to hone; it’s another to completely redefine.

(The CDC, as my friend Kevin Wilson pointed out, mostly does outstanding work. But they have a tendency to jump with both feet into moral panics. In this case, it’s the current debate about rape culture. Ten years ago, it was obesity. They put out a deeply flawed study that overestimated obesity deaths by a factor of 14. They quickly admitted their screwup but … guess which number has been quoted for the last decade on obesity policy?)

You might ask why I’m on about this. Surely any number of rapes is too many. The reason I wanted to talk about this, apart from my hatred of bogus studies, is that data influences policy. If you claim that 1.3 million women are being raped every year, that’s going to result in a set of policy decisions that are likely to be very damaging and do very little to address the real problem.

If you want a stat that means something, try this one: the incidence of sexual violence has fallen 85% over the last 30 years. That is from the FBI’s NCVS data so even if they are over- or under-estimating the amount of sexual violence, the differential is meaningful. That data tells you something useful: that whatever we are doing to fight rape culture, it is working. Greater awareness, pushing back against blaming the victim, changes to federal and state laws, changes to the emphasis of attorneys general’s offices and the rise of internet pornography have all been cited as contributors to this trend.

That’s why it’s important to push back against bogus stats on rape. Because they conceal the most important stat; the one that is the most useful guide for future policy and points the way toward ending rape culture.

The Pending Crash or How to Play with Scales:

Yesterday morning, I saw a chart claiming that the recent stock market trends are an eerie parallel of the run-up to the 1929 crash. I was immediately suspicious because, even if the data were accurate, we see this sort of crap all the time. There are a million people who have made a million bucks on Wall Street claiming to pattern match trends in the stock market. They make huge predictions, just like the Facebook study above. And those predictions are always wrong. Because, again, the out of sample data contains the real leverage.

This graph is even worse than that, though. As Quartz points out, the graph makers used two different y-axes. In one, the the 1928-29 rise of the stock market was a near doubling. In the other, the 2013-4 rise was an increase of about 25%. When you scale them appropriately, the similarity vanishes. Or, alternatively, the pending “crash” would be just an erasure of that 25% gain.

I’ve seen this quite a bit and it’s beginning to annoy me. Zoomed-in graphs of narrow ranges of the y-axis are used to draw dramatic conclusions about … whatever you want. This week, it’s the stock market. Next week, it’s global warming skeptics looking at little spikes on a 10-year temperature plot instead of big trends on a 150-year one. The week after, it will be inequality data. Here is one from Piketty and Saez, which tracks wealth gains for the rich against everyone else. Their conclusion might be accurate but the plot is useless because it is scaled to intervals of $5 million. So even if the bottom 90% were doing better, even if their income was doubling, it wouldn’t show up on the graph.

Halloween Linkorama

Three stories today:

  • Bill James once said that, when politics is functioning well, elections should have razor thin margins. The reason is that the parties will align themselves to best exploit divisions in the electorate. If one party is only getting 40% of the vote, they will quickly re-align to get higher vote totals. The other party will respond and they will reach a natural equilibrium near 50% I think that is the missing key to understanding why so many governments are divided. The Information Age has not only given political parties more information to align themselves with the electorate, it has made the electorate more responsive. The South was utterly loyal the Democrats for 120 years. Nowadays, that kind of political loyalty is fading.
  • I love this piece about how an accepted piece of sociology turned out to be complete gobbledygook.
  • Speaking of gobbledygook, here is a review of the article about men ogling women. It sounds like the authors misquoted their own study.
  • Rush is Wrong on Religion

    I see that Rush Limbaugh has dived into the latest climate nontroversy. That makes this is a good time to post this, which I wrote several months ago. Sorry to make this Global Warming Week. I hate that debate. But with the way the Daily Fail’s nonsense is propagating, I have no choice.

    Continue reading Rush is Wrong on Religion

    Mathematical Malpractice Watch: Cherry-Picking

    Probably one of the most frustrating mathematical practices is the tendency of politicos to cherry-pick data: only take the data points that are favorable to their point of view and ignore all the others. I’ve talked about this before but two stories circling the drain of the blogosphere illustrated this practice perfectly.

    The first is on the subject of global warming. Global warming skeptics have recently been crowing about two pieces of data that supposedly contradict the theory of global warming: a slow-down in temperature rise over the last decade and a “60% recovery” in Arctic sea ice.

    The Guardian, with two really nice animated gifs, show clearly why these claims are lacking. Sea ice levels vary from year to year. The long-term trend, however, has been a dramatic fall with current sea ice levels being a third of what they were a few decades ago (and that’s just area: in terms of volume it’s much worse with sea ice levels being a fifth of what they were). The 60% uptick is mainly because ice levels were so absurdly low last year that the natural year-to-year variation is equal to almost half the total area of ice. In other words, the variation in yearly sea levels has not changed — the baseline has shrunk so dramatically that the variations look big in comparison. This could easily — and likely will — be matched by a 60% decline. Of course, that decline will be ignored by the very people hyping the “recovery”.

    Temperature does the same thing. If you look at the second gif, you’ll see the steady rise in temperature over the last 40 years. But, like sea ice levels, planetary temperatures vary from year to year. The rise is not perfect. But each time it levels or even falls a little, the skeptics ignore forty years worth of data.

    (That having been said, temperatures have been rising much slower for the last decade than they were for the previous three. A number of climate scientists now think we have overestimated climate sensitivity).

    But lest you think this sort of thing is only confined to the Right …

    Many people are tweeting and linking this article which claims that Louis Gohmert spouted 12 lies about Obamacare in two minutes. Some of the things Gohmert said were not true. But other were and still others can not really be assessed at this stage. To take on the lies one-by-one:

    Was Obamacare passed against the will of the people?

    Nope. It was passed by a president who won the largest landslide in two decades and a Democratic House and Senate with huge majorities. It was passed with more support than the Bush tax cuts and Medicare Part D, both of which were entirely unfunded. And the law had a mostly favorable perception in 2010 before Republicans spent hundreds of millions of dollars spreading misinformation about it.

    The first bits of that are true but somewhat irrelevant: the Iraq War had massive support at first, but became very unpopular. The second is cherry-picked. Here is the Kaiser Foundation’s tracking poll on Obamacare (panel 6). Obamacare barely crested 50% support for a brief period, well within the noise. Since then, it has had higher unfavorables. If anything, those unfavorables have actually fallen slightly, not risen in response to “Republican lies”.

    Supporters of the law have devised a catch-22 on the PPACA: if support falls, it’s because of Republican money; if it rises it’s because people are learning to love the law. But the idea that there could be opposition to it? Perish the thought!

    Is Obamacare still against the will of American people?

    Actually, most Americans want it implemented. Only 6 percent said they wanted to defund or delay it in a recent poll.

    That is extremely deceptive. Here is the poll. Only 6% want to delay or defund the law because 30% want it completely repealed. Another 31% think it needs to be improved. Only 33% think the law should be allowed to take effect or be expanded.

    (That 6% should really jump out at you since it’s completely at variance with any political reality. The second I saw it, I knew it was garbage. Maybe they should have focus-group-tested it first to come up with some piece of bullshit that was at least believable.)

    Of the remaining questions, many are judgement calls on things that have yet to happen. National Memo asserts that Obamacare does not take away your decisions about health care, does not put the government between you and your doctor and will not keep seniors from getting the services they need. All of these are judgement calls about things that have yet to happen. There are numerous people — people who are not batshit crazy like Gohmert — who think that Obamacare and especially the IPAB will eventually create government interference in healthcare. Gohmert might be wrong about this. But to call it a lie when someone makes a prediction about what will happen is absurd. Let’s imagine this playing out in 2002:

    We rate Senator Liberal’s claim that we will be in Iraq for a decade and it will cost 5000 lives and $800 billion to be a lie. The Bush Administration has claimed that US troops will be on the ground for only a few years and expect less than a thousand casualties and about $2 billion per month. In fact, some experts predict it will pay for itself.

    See what I did there?

    Obamacare is a big law with a lot of moving parts. There are claims about how it is going to work but we won’t really know for a long time. Maybe the government won’t interfere with your health care. But that’s a big maybe to bet trillions of dollars on.

    The article correctly notes that the government will not have access to medical records. But then it is asserts that any information will be safe. This point was overtaken by events this week when an Obamacare site leaked 2400 Social Security numbers.

    See what I mean about “fact-checking” things that have yet to happen?

    Then there’s this:

    Under Obamacare, will young people be saddled with the cost of everybody else?

    No. Thanks to the coverage for students, tax credits, Medicaid expansion and the fact that most young people don’t earn that much, most young people won’t be paying anything or very much for health care. And nearly everyone in their twenties will see premiums far less than people in their 40s and 50s. If you’re young, out of school and earning more than 400 percent of the poverty level, you may be paying a bit more, but for better insurance.

    This is incorrect. Many young people are being coerced into buying insurance that they wouldn’t have before. As Avik Roy has pointed out, cheap high-deductible plans have been effectively outlawed. Many college and universities are seeing astronomical rises in health insurance premiums, including my own. The explosion of invasive wellness programs, like UVAs, has been explicitly tied to the PPACA. Gohmert is absolutely right on this one.

    The entire point of Obamacare was to get healthy people to buy insurance so that sick people could get more affordable insurance. That is how this whole thing works. It’s too late to back away from that reality now.

    Does Obamacare prevent the free exercise of your religious beliefs?

    No. But it does stop you from forcing your beliefs on others. Employers that provide insurance have to offer policies that provide birth control to women. Religious organizations have been exempted from paying for this coverage but no one will ever be required to take birth control if their religion restricts it — they just can’t keep people from having access to this crucial, cost-saving medication for free.

    This is a matter of philosophy. Many liberals think that if an employer will not provide birth control coverage to his employees, he is “forcing” his religious views upon them (these liberals being under the impression that free birth control pills are a right). I, like many libertarians and conservatives (and independents), see it differently: that forcing someone to pay for something with which they have a moral qualm is violating their religious freedom. The Courts have yet to decide on this.

    I am reluctant to call something a “lie” when it’s a difference of opinion. Our government has made numerous allowance for religious beliefs in the past, including exemptions from vaccinations, the draft, taxes and anti-discrimination laws. We are still having a debate over how this applies to healthcare. Sorry, National Memo, that debate isn’t over yet.

    So let’s review. Of Gohmert’s 12 “lies”, the breakdown is like so:

    Lies: 4
    Debatable or TBD: 5
    Correct: 3
    Redundant: 1

    (You’ll note that’s 13 “lies”; apparently National Memo can’t count).

    So 4 only out of 13 are lies. Hey, even Ty Cobb only hit .366

    Mathematical Malpractice: Focus Tested Numbers

    One of the things I keep encountering in news, culture and politics are numbers that appear to be pulled out of thin air. Concrete numbers, based on actual data, are dangerous enough in the wrong hands. But when data get scarce, this doesn’t seem to intimidate advocates and some social scientists. They will simply commission a “study” that produces, in essence, any number they want.

    What is striking is that the numbers seem to be selected with the diligent care and skill that the methods lack.

    The first time I became aware of this was with Bill Clinton. According to his critics — and I can’t find a link on this so it’s possibly apocryphal — when Bill Clinton initiated competency tests for Arkansas teachers, a massive fraction failed. He knew the union would blow their stack if the true numbers were released so he had focus groups convened to figure out what percentage of failures was expected, then had the test curved so that the results met the expectation.

    As I said, I can’t find a reference for that. I seem to remember hearing it from Limbaugh, so it may be a garbled version (I can find lawsuits about race discrimination with the testing, so it’s possible a mangled version of that). But the story struck me to the point where I remember it twenty years later. And the reason it struck is because:

  • It sounds like the sort of thing politicians and political activists would do.
  • It would be amazingly easy to do.
  • Our media are so lazy that you could probably get away with it.
  • Since then, I’ve seen other numbers which I call “focus tested numbers” even tough they may not have been run by focus groups. But they cross me as numbers derived by someone coming up with the number first and then devising the methodology second. They first part is the critical one. Whatever the issue is, you have to come with a number that is plausible and alarming without being ridiculous. Then you figure out the methods to get the number.

    Let’s just take an example. The first time I became aware of the work of Maggie McNeill was her thorough debunking of the claim that 200,000 underage girls are trafficked for sex in the United States. You should read that article, which comes to an estimate of about 15,000 total underage prostitutes (most which are 16 or 17) and only a few hundred to a few thousand that are trafficked in any meaningful sense of that word. That does not make the problem less important, but it does make it less panic-inducing.

    But the 200,000 number jumped out at me. Here’s my very first comment on Maggie’s blog and her response:

    Me: Does anyone know where the 100,000 estimate comes from? What research it’s based on?

    It’s so close to 1% [of total underage girls] that I suspect it may be as simple as that. We saw a similar thing in the 1980′s when Mitch Snyder claimed (and the media mindlessly repeated) that three million Americans were homeless (5-10 times the estimates from people who’d done their homework). It turned out the entire basis of that claim was that three million was 1% of the population.

    This is typical of the media. The most hysterical claim gets the most attention. If ten researchers estimates there are maybe 20,000 underage prostitutes and one big-mouth estimates there are 300,000, guess who gets a guest spot on CNN?

    —–

    Maggie: Honestly, I think 100,000 is just a good large number which sounds impressive and is too large for most people to really comprehend as a whole. The 300,000 figure appears to be a modification of a figure from a government report which claimed that something like 287,000 minors were “at risk” from “sexual exploitation” (though neither term was clearly defined and no study was produced to justify the wild-ass guess). It’s like that game “gossip” we played as children; 287,000 becomes 300,000, “at risk” becomes “currently involved” and “sexual exploitation” becomes “sex trafficking”. 🙁

    The study claimed that 100-300,000 girls were “at risk” of exploitation but defined “at risk” so loosely that simply living near a border put someone at risk. With such methods, the authors could basically claim any number they wanted. After reading that analysis and picking my jaw up off of the floor, I wondered why anyone would do it that way.

    And then it struck me: because the method wasn’t the point; the result was. Even the result wasn’t the point; the issue they wanted to advocate was. The care was not in the method: it was in the number. If they had said that there were a couple of thousand underage children in danger, people would have said, “Oh, OK. That sounds like something we can deal with using existing policies and smarter policing.” Or even worse, they might have said, “Well, why don’t we legalize sex work for adults and concentrate on saving these children?” If they had claimed a million children were in danger, people would have laughed. But claim 100-300,000? That’s enough to alarm people into action without making them laugh. It’s in the sweet spot between the “Oh, is that all?” number of a couple thousand and the “Oh, that’s bullshit” number of a million.

    Another great example was the number SOPA supporters bruted about to support their vile legislation. Julian Sanchez details the mathematical malpractice here. At first, they claimed that $250 billion was lost to piracy every year. That number — based on complete garbage — was so ridiculous they had to revise it down to $58 billion. Again, notice how well-picked that number is. At $250 billion, people laughed. If they had gone with a more realistic estimate — a few billion, most likely — no one would have supported such draconian legislation. But $58 billion? That’s enough to alarm people, not enough to make them laugh and — most importantly — not enough to make the media do their damn job and check it out.

    I encountered it again today. The EU is proposing to put speed limiters on cars. Their claim is this will cut traffic deaths by a third. Now, we actually do have some data on this. When the national speed limit was introduced in America, traffic fatalities initially fell about 20%, but then slowly returned to normal. They began falling again, bumped up a bit when Congress loosened the law, then leveled out in the 90’s and early 00’s after Congress completely repealed the national speed limit. The fatality rate has plunged over the last few years and is currently 40% below the 1970’s peak — without a speed limit.

    That’s just raw numbers, of course. In real terms — per million vehicle miles driven — fatalities have plunged almost 75% of the last forty years, with no effect of the speed limit law. Of course, more cars contain single drivers than ever before. But even on a per capita basis, car fatalities are half of what they once were.

    That’s real measurable progress. Unfortunately for the speed limiters, it’s result of improved technology and better enforcement of drunk driving laws.

    So the claim that deaths from road accidents will plunge by a third because of speed limits is simply not supported by data in the United States. They might plunge as technology, better roads and laws against drunk driving spread to Eastern Europe. And I’m sure one of the reasons they are pushing for speed limits is that they can claim credit for that inevitable improvement. But a one-third decline is just not realistic.

    No, I suspect that this is a focus tested number. If they claimed fatalities would plunge by half, people would laugh. If they claimed 1-2%, no one would care. But one-third? That’s in the sweet spot.

    Bulbs

    I have quite a few posts in the queue that will come out in the next few weeks but this has been my quietest month ever on the blog. One thing I did want to post on, however, came to a head tonight. While working in the basement, I knocked over a basket of bulbs and one shattered. Of course, it was a CFL with mercury in it so I had to follow the EPA’s elaborate instructions for cleaning up. Because it was the basement, I couldn’t take the most important step — airing out the room.

    Of course, the amount of mercury in CFL’s is very small — a couple of mg. I probably got ten times the exposure when I dropped and broke a mercury thermometer as a kid and then played with the mercury for a while. But still, these things were foisted on us and encouraged before anyone had really explained the potential danger (in parts of the world, they’re now mandatory). The EPA has done an analysis showing that, on balance, less mercury will be released into the environment because of the decreased amount of coal burnt to power the bulbs. However, I’m not sure this analysis is accurate since 1) history shows that greater energy efficiency mostly results in us using more powered devices: energy use tends to rise or be flat; 2) coal is slowly dying an industry. Powered by gas or nuclear, it’s likely that CFL’s will put more mercury into the environment. It also ignores the aspect that having mercury in the air from power plants is a little different from having it on the floor where your children play.

    LED bulbs are better but … they have their own concerns, which no one talks about.

    Global warming is real — one of my queued posts is on that subject. But the environmental movement has become fixated on it almost to the exclusion of all else. There is no such thing as perfect technology. Wind and solar require dirty manufacturing techniques and extensive use of rare-earth elements (that have to be mined). Nuclear has its obvious dangers. Fracking is less carbon-intense than coal, but doesn’t come without its own set of risks.

    The problem is that we do not talk about these trade-offs. We don’t balance rare-earth mining versus radioactive waste versus carbon emissions. We simply get into tizzies about global warming or nuclear waste and stampede toward something that looks good. And that extends into the home. On balance, I might take an LED or CFL light because it saves money, saved energy and the toxin risk is low. But that choice should not be mandated. People should be free to make their own evaluations of the tradeoffs.

    Saturday Linkorama

  • This visualization of the Right of Spring is seriously seriously cool. Seeing the music like that, you start hearing the subtleties that elude you when you just hear it. This is one of the reasons I like to see classical music in performance. There is so much more going on than the ear can take in.
  • This map of linguistic divides in the United States, is something I could spend an entire post on. I match most of the pronunciations from Georgia except for “lawyer” and “pajamas”.
  • This story, about charities that just exist to raise money, should be getting national attention. It’s a disgrace.
  • I’ve used some of these.
  • Roman concrete was apparently better than the shit we’re using.
  • I think this is more or less true: the financial industry has stopped being about enabling economic progress and more about itself. When engineers can make more moving piles of money around than inventing things, we’ve got a problem.
  • Teenage boys killed the sex scene.
  • There’s Vitamins and then There’s Vitamins

    Note from Mike: I recently tweeted an NYT story that claims deleterious health effects from consuming too many vitamins with the note that I thought it likely people were gobbling too many pills. My wife decided the article merited a response.

    This NYT article on vitamins contained a few scientific issues that I feel the need to respond to. Unfortunately, the NYT didn’t allow opinions to be expressed so you will have to endure my ranting and raving.

    The article provides details about published studies, two of which are published in The New England Journal of Medicine, that claim deleterious effects from excessive vitamin consumption. These studies show that those that took Vitamin A or beta carotene (Vitamin K) supplements were more likely to die from lung cancer or heart disease compared to those who didn’t. The article also lists other studies showing a correlation between taking Vitamin A, E, beta carotene (Vitamin K), Vitamin C and selenium supplements and mortality. The author then goes on the say the link between mortality and the vitamins ingested are antioxidants.

    I cannot agree with this conclusion as this conflates fat soluble vitamins and water soluble vitamins and minerals. Vitamins A, D, E and K are fat soluble meaning any excess taken in the diet is stored in the fat of an individual and the body can’t regulate these nearly as well as the water soluble ones. Selenium is water soluble, as are the Vitamins B and C. An excess of a water soluble vitamin or mineral is removed in the urine by the body. I can therefore see the disease and mortality states arising from fat soluble vitamins. But I am concerned that the studies showing consuming the water soluble vitamins plus Vitamin C and selenium came to the wrong conclusion. It may be a case of guilt by association with the fat soluble vitamins. Have any studies looked at water soluble vitamins in isolation?

    I worry about this because there are benefits to high vitamin levels for certain conditions. The third paragraph claims:

    Nutrition experts argue that people need only the recommended daily allowance — the amount of vitamins found in a routine diet. Vitamin manufacturers argue that a regular diet doesn’t contain enough vitamins, and that more is better.

    Up until I was diagnosed with multiple sclerosis (MS), I would have subscribed to the nutrition experts’ opinion as well. But after turning my research interests towards the genetic underpinnings of MS (I am a medical geneticist), I quickly uncovered how vital Vitamin D is in the management of the relapse-remitting disease. I even tried getting out in the sun in the summer and turned to tanning beds in the winter to maximize my body producing enough Vitamin D to manage my MS without resorting to Vitamin D supplements. After many flare ups over a two to three year period, the last of which put me in a wheelchair in the summer time, my Vitamin D level came back each time as below optimal levels. For this reason, I now take four times the FDA recommended level of Vitamin D in a supplement form to help manage my MS. Over the past year of doing this, I can report, my MS is well managed without any flare ups. For this reason, I think that the levels listed on the recommended daily allowance are not adequate for people with medical conditions needing additional supplements.

    I consume a prescription strength dose of folate, vitamin B12 and Vitamin B6 for overcoming the chance of a miscarriage while I carry my second child. After three miscarriages, I was recently diagnosed as being a carrier of a gene known to be involved with miscarriages as well as migraines, cardiovascular disease and other disorders. To overcome this reduced gene function, more Vitamin B is needed to reduce homocysteine levels in the body. Since Vitamin B is a water soluble vitamin, I am also supplementing it with the consumption of spinach, which does not contain much Vitamin B12 or Vitamin B6, just folic acid (folate). Since my taste for spinach is waning, I rely on the supplement strength pill for these additional vitamins as I know my body can self regulate the concentration of these vitamins without much harm to the baby. Similarly, my husband also has the same genetic abnormality and suffers from migraines. To treat this disease, we buy an over the counter Vitamin B supplement for his symptom management at not much cost to us versus the prescription strength pill that I take.

    This is why calling on the FDA to better regulate vitamin supplement sales makes me a bit nervous. If the FDA becomes involved in this fight, I worry that the ability to self regulate symptom management for diseases and disorders may be impaired. Tighter regulation of the fat soluble vitamins may be justified. But it is not obvious that tighter regulation of water soluble vitamins is.

    Late May Linkorama

  • A brief bit of mathematical malpractice, although not a deliberate one. The usually smart Sarah Kliff cites a study that of an ER that showed employees spent nearly 5000 minutes on Facebook. Of course, over 68 computers and 15 days, that works out to about 4 minutes per day per computer which … really isn’t that much.
  • What’s interesting about the Netflix purge is that many of the studios are pulling movies to start their own streaming services. This is idiotic. I’m pretty tech savvy and I have no desire to have 74 apps on my iPad, one for each studio. If I want to watch a movie, I’m going to Netflix or Amazon or iTunes, not a studio app (that I have to pay another subscription fee for). In fact, many days my streaming is defined by opening up the Netflix app and seeing what intrigues me.
  • We go into this on Twitter. The NYT ran an article about how little nutrition our food has. Of course, they have defined “nutritional content” as the amount of pigment which has dubious nutritional value (aside from anti-oxidant value; so, no nutritional value). As Kevin Wilson said according to the graph, the value of blue corn is that it is blue and not yellow.
  • While we’re on the subject of nutrition, it turns out that low sodium intake may not only not be beneficial, it may even be harmful. I’m slowly learning that almost everything we think we know about nutrition is shaky at best.
  • Ultra-conserved words. I am fascinated by language.
  • Wine tasting is bullshit.
  • How the peaceful loving people-friendly Soviet Union tried to militarize space.
  • The most remote places in each state.
  • Porn is not the problem. You are. More on how “sex addiction” is a made up disorder.
  • Meet the coins that could rewrite history. Every time we learn more about the past, we find out that our ancestors were smarter and more adventurous than we thought they were. And some people think they needed aliens to build the pyramids.
  • The Law of BS

    Some time ago, I talked about my Rule of Expertise. I’m in the process of catching up on old posts from Bill James’ website. The article I refer to is behind a firewall. It’s about the Jeffrey MacDonald case. But in the course of it, Bill says something utterly brilliant:

    There are certain characteristics of bullshit, and there are certain characteristics of the truth. The truth tends to be specific; bullshit tends to be vague and imprecise. The truth tends to involve facts that can be checked out; bullshit is always built around things that you have no way of checking out. The truth tends to be told consistently, the same from one day to the next; bullshit changes every time it is told. Stable, responsible honest people tend to tell the truth; unstable, dishonest, unreliable people tend to bullshit. The truth is coherent and logical; bullshit is incoherent and illogical.

    Almost everything I said in my Law of Expertise post could be considered a subset of that general rule. When an “expert” tells you what a great expert he is, he’s spewing vague bullshit. Real experts tend to be specific, consistent and verifiable.

    However…

    I think the equation has changed a bit in the Information Age. The internet has a long memory and this has forced the bullshitters to be more consistent and more specific. The result is that BS now gets debunked faster than ever. However, it has also allowed BS to assume a facade of truth that fools some people.

    Think about vaccine hysteria. The lies are specific, consistent and seem to involve facts. That makes people believe it, even after thorough and unremitting debunking.

    (I should note, in passing, that the MacDonald case is of particular interest to me. My dad was — and still is, as far as I know — convinced that MacDonald was an innocent man railroaded by a biased judge, a vindictive prosecutor, a slimy writer and a vengeful father-in-law. I was convinced of that myself until I read Weingarten’s post, which pointed out that there is almost no evidence to prove MacDonald’s contention that his family was murdered by a bunch of hippies and that all the extant evidence — including recently tested tissue under the wife’s fingernails — supports the prosecution case. It’s kind of rare that I disagree with my dad on something like this, but … I do. The prosecution was able to put together a scenario consistent with the evidence (although I don’t buy the amphetamines angle). The defense wasn’t.

    However, while I am mostly convinced that MacDonald probably did murder his family, I’m not as sure that he should have been convicted. The crime scene was not properly secured, for one and exculpatory evidence might have been destroyed. The judge did seem biased against MacDonald. And I do think Bill James (and Megan McArdle) make a good point about prosecutions — once they focus on a suspect, they develop a tunnel vision which sees everything in light of that suspicion. James’ makes what I think is the most important point: the prosecution’s case fits together extremely well … if you assume that MacDonald was the killer.

    It’s an awful case and probably one of the reasons it fascinates so many people. On the one hand, you could have an innocent man convicted of one of the most heinous crimes a man can commit. On the other hand, you have a man committing one of the most heinous crimes a man can commit, including the deliberate murder of a sleeping toddler.

    In any case, you should subscribe to James’ site if you have even a mild interest in baseball. Baseball analysis is only part of what he offers.)

    Sunday Linkorama

  • A fascinating look at how dollar bills move, courtesy of the Where’s George website. I find it fascinating the Pennsylvania is divided in half.
  • This is what I mean by Sports Media Twerp. They are never wrong and everybody else is just an idiot.
  • Really interesting blog on the least visited countries in the world. The writer is trying to visit every country at least once. Wish I had the resources for that.
  • I wish climate scientists would not overstate their conclusions. It makes it so much easier for people to pretend global warming is a hoax.
  • John McWhorter has a great article disputing the notion that texting is destroying the English language.
  • The contention that FDR was anti-semitic does not really surprise me. Years ago I read a book called While Six Million Died that detailed, point by point, how FDR did almost nothing to stop or prevent the Holocaust. It was only when members of his own Administration confronted him over foot-dragging on the issue of saving Romanian Jews that he did anything. He defeated Hitler, of course, which was why he became a hero to my grandparents’ generation. But the idea that he was immune from the anti-semitism that gripped much of the country and the world is absurd.
  • Fascinating and kind of frightening photo essay of high-density living. Think of all the stories you see in each picture.