Quotulatiousness

April 21, 2015

The statistical anomalies of sex

Filed under: Health,Randomness — Tags: , — Nicholas @ 03:00

As the old saying has it, “everyone lies about sex“:

Straight men have had twice as many sexual partners, on average, as straight women. Sounds plausible, seeing that men supposedly think about sex every seven seconds. Except that it’s mathematically impossible: in a closed population with as many men as women (which roughly there are) the averages should match up. Someone is being dishonest, but who? And why? These questions, along with many others, are explored in Sex by numbers, a new book by David Spiegelhalter, Winton Professor for the Public Understanding of Risk at the University of Cambridge.

“Sex is a great topic,” says Spiegelhalter. “There’s lots of it going on, but we don’t know what goes on or how much of it, because most of the time it goes on behind closed doors. It’s a really difficult topic to investigate scientifically, and a real challenge for statistics.” Spiegelhalter’s aim is to get people interested in a critical approach to the numbers they hear about in the news and give them the tools to figure out if they can be believed. “It’s really a book about statistics, using sex as an example.”

Statistics about sex are not all equally good. Some, like the number of births in a given year, are cast-iron facts, but others are much harder to come by. The number of sexual partners is a good example. The mismatch above comes from the third The National Survey of Sexual Attitudes and Lifestyles (Natsal), conducted between 2010 and 2012, in which men reported having had 14 sexual partners, on average, and women 7. Studies have suggested that women give lower numbers when they fear the survey isn’t entirely confidential, something that doesn’t seem to affect men (contrary to my expectation, it doesn’t induce them to exaggerate). So that’s one possible explanation for the mismatch: sadly, women still need to fear social stigma.

But there are other explanations too. One is that men (more than women) may have some of their sexual experience with sex workers. These aren’t included in the surveys, so their experiences are missing from the female tally. Another is that there are different attitudes as to what counts as a sexual partner. If a woman feels she’s been coerced by a man, for example, she may not want to count him.

April 18, 2015

Correlation, causation, and lobby money

Filed under: Business,Health,Media — Tags: , , — Nicholas @ 02:00

Tim Harford‘s latest column on tobacco, research, and lobby money:

It is said that there is a correlation between the number of storks’ nests found on Danish houses and the number of children born in those houses. Could the old story about babies being delivered by storks really be true? No. Correlation is not causation. Storks do not deliver children but larger houses have more room both for children and for storks.

This much-loved statistical anecdote seems less amusing when you consider how it was used in a US Senate committee hearing in 1965. The expert witness giving testimony was arguing that while smoking may be correlated with lung cancer, a causal relationship was unproven and implausible. Pressed on the statistical parallels between storks and cigarettes, he replied that they “seem to me the same”.

The witness’s name was Darrell Huff, a freelance journalist beloved by generations of geeks for his wonderful and hugely successful 1954 book How to Lie with Statistics. His reputation today might be rather different had the proposed sequel made it to print. How to Lie with Smoking Statistics used a variety of stork-style arguments to throw doubt on the connection between smoking and cancer, and it was supported by a grant from the Tobacco Institute. It was never published, for reasons that remain unclear. (The story of Huff’s career as a tobacco consultant was brought to the attention of statisticians in articles by Andrew Gelman in Chance in 2012 and by Alex Reinhart in Significance in 2014.)

Indisputably, smoking causes lung cancer and various other deadly conditions. But the problematic relationship between correlation and causation in general remains an active area of debate and confusion. The “spurious correlations” compiled by Harvard law student Tyler Vigen and displayed on his website (tylervigen.com) should be a warning. Did you realise that consumption of margarine is strongly correlated with the divorce rate in Maine?

April 16, 2015

Measuring productivity in the modern economy

Filed under: Economics — Tags: , , , — Nicholas @ 03:00

Tim Worstall on how our traditional economic measurements are less and less accurate for the modern economic picture:

… in the developed countries there’s a problem which seems to me obvious (and Brad Delong has even said that I’m right here which is nice). Which is that we’re just not measuring the output of the digital economy correctly. For much of that output is not in fact priced: what Delong has called Andreessenian goods (and Marc Andreessen himself calls Mokyrian). For example, we take Google’s addition to the economy to be the value of advertising that Google sells, not the value in use of the Google search engine. Similarly, Facebook is valued at its advertising sales, not whatever value people gain from being part of a social network of 1.3 billion people. In the traditional economy that consumer surplus can be roughly taken to be twice the sales value of the goods. For these Andreessenian goods the consumer surplus could be 20 times (Delong) or even 100 times (my own, very controversial and back of envelope calculations) that sales value.

We are therefore, in my view, grossly underestimating output. And since we measure productivity as the residual of output and resources used to create it we’re therefore also grossly underestimating productivity growth. We’re in error by using measurements of the older, physical, economy as our metric for the newer, digital, one.

In short, I simply don’t agree that growth is as slow as we are measuring it to be. Thus any predictions that rely upon taking our current “low” rate of growth as being a starting point must, logically, be wrong. And that also means that all the policy prescriptions that flow from such an analysis, that we must spend more on infrastructure, education, government support for innovation, must also be wrong.

April 2, 2015

How do we measure prosperity? Badly

Filed under: Economics,History,Technology — Tags: , — Nicholas @ 05:00

At Coyote Blog, Warren Meyer points out that we do not have a useful way to measure prosperity:

GDP growth and unemployment reduction are terrible measures. Just to give one example, these measures looked fabulous in WWII. But the average person living in the US had access to almost nothing — they couldn’t buy anything under rationing, they couldn’t travel for leisure, etc. GDP looked great because we were building stuff and then blowing it up, the economic equivalent of digging a hole and filling it in (but worse, because people were dying). And unemployment looked great because we had drafted everyone and sent them off to get shot.

[…]

How do we take into account that even if a person has the same income as someone in 1952, they are effectively wealthier in many ways due to access to medical procedures, travel, entertainment, electronic devices, etc?

Somehow we need to measure consumer capability — not just how much raw money one has but what can one do with the money? What is the horizon of possibilities? Deirdre McCloskey tends to eschew the term capitalism in favor of “market-tested innovation.” I think that is a pretty powerful description of our system. But if it is, we really are only measuring the impact of productivity and cost-reduction innovations. How do we measure the wealth impact of consumer-empowerment innovations like iPhones? Essentially, we don’t. Which, by the way, may be one reason our current crappy metrics say we have growing income inequality. With our current metrics, Steve Jobs’ increase in wealth is noted in the metrics, but the metrics don’t show the rest of us getting any wealthier by the fact that we can now have iPhones (or the myriad of competitors the iPhone spawned). The consumer surplus from iPhones undoubtedly dwarfs the money Jobs made, but it doesn’t show up in any wealth calculations.

March 19, 2015

There’s a deep-seated problem with how we measure the so-called “standard of living”

Filed under: Economics,History — Tags: , — Nicholas @ 04:00

My family are tired of hearing me say any variation on the expression “the past is a foreign country”, but I ring the changes on that phrase because it at least frames some of the problem we have in trying to comprehend just how much life has changed even within living memory, never mind more than a couple of generations ago. At the Cato Institute, Megan McArdle tries to avoid saying exactly those words, but the sense is still very much the same:

The generation that fought the Civil War paid an incredible price: one in four soldiers never returned home, and one in thirteen of those who did were missing one or more limbs. Were they better off than their parents’ generation? What about the generation that lived through the Great Depression, many of whom graduated into World War II? Does a new refrigerator and a Chevrolet in the driveway make up for decades and lives lost to the march of history? Or for the rapid increase in crime and civic disorder that marked the postwar boom? Then again, what about African Americans, who saw massive improvements in both their personal liberty and their personal income?

We should never pooh-pooh economic progress. As P.J. O’Rourke once remarked, I have one word for people who think that we live in a degenerate era fallen from a blessed past full of bounty and ease, and that word is “dentistry.” On the other hand, we should not reduce standard of living to (appropriately inflation adjusted) GDP numbers either. Living standards are complicated, and the tools we have to measure what is happening to them are almost absurdly crude. I certainly won’t achieve a satisfying measure in this brief essay. But we can, I think, begin to sketch the major ways in which things are better and worse for this generation. Hopefully we can also zero in on what makes the current era feel so deprived, and our distribution of income so worrisome.

My grandfather worked as a grocery boy until he was 26 years old. He married my grandmother on Thanksgiving because that was the only day he could get off. Their honeymoon consisted of a weekend visiting relatives , during which they shared their nuptial bed with their host’s toddler. They came home to a room in his parents’ house—for which they paid monthly rent. Every time I hear that marriage is collapsing because the economy is so bad, I think of their story.

By the standards of today, my grandparents were living in wrenching poverty. Some of this, of course, involves technologies that didn’t exist—as a young couple in the 1930s my grandparents had less access to health care than the most neglected homeless person in modern America, simply because most of the treatments we now have had not yet been invented. That is not the whole story, however. Many of the things we now have already existed; my grandparents simply couldn’t afford them. With some exceptions, such as microwave ovens and computers, most of the modern miracles that transformed 20th century domestic life already existed in some form by 1939. But they were out of the financial reach of most people.

If America today discovered a young couple where the husband had to drop out of high school to help his father clean tons of unsold, rotted produce out of their farm’s silos, and now worked a low-wage, low-skilled job, was living in a single room with no central heating and a single bathroom to share for two families, who had no refrigerator and scrubbed their clothes by hand in a washtub, who had serious conversations in low voices over whether they should replace or mend torn clothes, who had to share a single elderly vehicle or make the eight-mile walk to town … that family would be the subject of a three-part Pulitzer prize winning series on Poverty in America.

But in their time and place, my grandparents were a boring bourgeois couple, struggling to make ends meet as everyone did, but never missing a meal or a Sunday at church. They were excited about the indoor plumbing and electricity which had just been installed on his parents’ farm, and they were not too young to marvel at their amazing good fortune in owning an automobile. In some sense they were incredibly deprived, but there are millions of people in America today who are incomparably better off materially, and yet whose lives strike us (and them) as somehow objectively more difficult.

March 16, 2015

Comparing statistics from different sources

Filed under: Economics,Government,USA — Tags: , — Nicholas @ 03:00

In Forbes, Tim Worstall points out that you need to be careful in using statistics sourced from different organizations or agencies, as they don’t necessarily measure quite the same thing, despite the names being very similar:

There are certain sets of statistics put out (largely by the OECD nations like the US and so on) which we really can believe as saying exactly what is indicated upon the tin.

However, that isn’t the same as saying that we should be willing to just accept all such US or OECD statistical numbers. Take, for example and this is one that I have banged on about for many a year now, The US and other OECD measures of poverty. The standard OECD measure of who is in poverty is below 60% of median income, adjusted for housing costs and household size. This is a measure of inequality, not actual poverty. It is also after all of the things that are done to reduce poverty, benefits, redistribution and all that. The US measure is, again adjusted for household size but not for housing costs, a measure of actual poverty. It is not related to average incomes but to what was low income in the early 1960s updated for inflation. And more significantly, it is before almost all of the things done to try to alleviate poverty. The OECD poverty measure is thus a measure of how much (relative) poverty there is after the things done to reduce poverty and the US standard number is a measure of how much absolute poverty there is before attempts to reduce poverty.

There’s nothing particularly wrong with either measure. But we’ve got to be very careful in acknowledging the difference between the two before we go and do something stupid like directly compare them, US poverty rates against the poverty rates of other OECD countries. Yet we do in fact see such comparisons being made all the time.

Another such little mistake of current interest is the way that we’re continually told that US average wages haven’t risen for decades. And it’s true, in one sense, that they haven’t. But wages aren’t actually what we should be looking at: total compensation from work is. And that’s been rising reasonably nicely over that same time period. The difference is in the benefits that we get over and above our wages from going to work. That health care insurance for example. This is more a matter of manipulation in the presentation of the statistics and if you see someone bleating about “wages” be very careful to check and see whether they are talking about what is of interest, compensation, or about wages which is a sign that they’re trying to mislead.

February 21, 2015

QotD: Campbell’s Law

Filed under: Business,Quotations — Tags: , , — Nicholas @ 01:00

The most common problem is that all these new systems — metrics, algo­rithms, automated decisionmaking processes — result in humans gaming the system in rational but often unpredictable ways. Sociologist Donald T. Campbell noted this dynamic back in the ’70s, when he articulated what’s come to be known as Campbell’s law: “The more any quantitative social indicator is used for social decision-making,” he wrote, “the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.”

On a managerial level, once the quants come into an industry and disrupt it, they often don’t know when to stop. They tend not to have decades of institutional knowledge about the field in which they have found themselves. And once they’re empowered, quants tend to create systems that favor something pretty close to cheating. As soon as managers pick a numerical metric as a way to measure whether they’re achieving their desired outcome, everybody starts maximizing that metric rather than doing the rest of their job — just as Campbell’s law predicts.

Felix Salmon, “Why Quants Don’t Know Everything”, Wired, 2014-01-14

January 22, 2015

China (barely) misses growth target … as if we can trust their numbers anyway

Filed under: China,Economics,Government — Tags: , , , — Nicholas @ 04:00

Ah, well, I haven’t ridden this old hobby horse for a while, so let’s just let Tim Worstall explain why this time, we might be able to get a bit of perspective from the otherwise unreliable official Chinese government economic figures:

Many observers have been slightly sceptical of Chinese GDP numbers for some years now. Regional GDP numbers don’t seem to quite match with other regional numbers (say, oil consumption, other proxies for economic activity) and national numbers don’t necessarily reflect the sum of all of those regional numbers either. There’s absolutely no doubt at all that the place has been getting richer but whether quite so much or quite in the manner being reported is another matter. And then there’s another group of observers (this one including myself) who have some experience of how communists report economic numbers. There’s a plan, the Communist Party is in charge of executing that plan and, amazingly, the plan is always reported to have either worked or been exceeded. Anything less would reflected badly on said Communist Party. As I’ve also been exposed to the old Soviet accounting systems I’m more sceptical than most on this point.

So, there’s that slight worry that a slowing China (or one not growing at the former breakneck pace perhaps) will also lower growth in other countries. We’re pretty sure that’s going to happen. But we’ve also got this other thing to ponder. If the Communist Party is allowing the reporting of numbers that don’t meet the plan then what’s going on with that?

Is this some sea change in the management of the numbers? They’re actually reporting the correct numbers? Or are those suspected massages of the numbers still going on but they underlying reality is so bad that they just couldn’t get up to the planned target? This is, I agree, all wild surmise. But it is a surprise that the numbers came in below target because that’s just not what we’ve come to expect in such a political system. And that could be very bad news indeed.

December 10, 2014

US child poverty is bad … but nowhere near as bad as they say

Filed under: Media,USA — Tags: , , , , — Nicholas @ 00:04

Tim Worstall debunks a headline statistic from earlier this month:

We’ve a new report out from the Mailman School of Public Health telling us that in some urban parts of the US child poverty is up at the unbelievable rates of 40, even 50% or more. The problem with this claim is that it’s simply not true. Apparently the researchers aren’t quite au fait with how poverty is both defined and alleviated in the US. Which is, when you think about it, something of a problem for those who decide to present us with statistics about child poverty.

[…]

Everyone else [in the world] (as well as using a relative poverty standard, usually below 60% of median earnings adjusted for family size) measures poverty after the effects of the tax and benefits systems on alleviating poverty. So, in my native UK if you’re poor you might get some cash payments (say, unemployment pay), some tax credits, help with your housing costs (housing benefit we call it), reduced property taxes (council tax credit) and so on. Whether you are poor or not is defined as being whether you are still under that poverty level after the effects of all of those attempts to alleviate poverty.

In the US things are rather different. It’s an absolute standard of income (set in the 1960s and upgraded only for inflation, not median incomes, since) but it counts only market income plus direct cash transfers to the poor before measuring against that standard. Thus, when we measure the US poor we do not include the EITC (equivalent of those UK tax credits, indeed our UK ones were copied from the US), we do not include Section 8 vouchers (housing benefit), Medicaid, we don’t even include food stamps. Because the US measure of poverty simply doesn’t include the effects of benefits in kind and through the tax system.

The US measure therefore isn’t the number of children living in poverty. It’s the number of children who would be in poverty if there wasn’t this system of government alleviation of poverty. When we do actually take into account what is done to alleviate child poverty we find that it’s really some 2-3% of US children who live in poverty. Yes, that low: the US welfare state is very much child orientated.

(Emphasis mine)

November 14, 2014

Either kink is now pretty much mainstream … or Quebec is a hotbed of kinksters

Filed under: Cancon,Health — Tags: , , , , , — Nicholas @ 07:24

In Reason, Elizabeth Nolan Brown reviews the findings of a recent survey on what kind of kinks are no longer considered weird or unusual (because so many people fantasize about ’em or are actively partaking of ’em):

Being sexually dominated. Having sex with multiple people at once. Watching someone undress without their knowledge. These are just a few of the totally normal sexual fantasies uncovered by recent research published in the Journal of Sexual Medicine. The overarching takeaway from this survey of about 1,500 Canadian adults is that sexual kink is incredibly common.

While plenty of research has been conducted on sexual fetishes, less is known about the prevalence of particular sexual desires that don’t rise to the level of pathological (i.e., don’t harm others or interfere with normal life functioning and aren’t a requisite for getting off). “Our main objective was to specify norms in sexual fantasies,” said lead study author Christian Joyal. “We suspected there are a lot more common fantasies than atypical fantasies.”

Joyal’s team surveyed about 717 Québécois men and 799 women, with a mean age of 30. Participants ranked 55 different sexual fantasies, as well as wrote in their own. Each fantasy was then rated as statistically rare, unusual, common, or typical.

Of course, the statistics also show where men and women differ in some areas:

Notably, men were more likely than women to say they wanted their sexual fantasies to become sexual realities. “Approximately half of women with descriptions of submissive fantasies specified that they would not want the fantasy to materialize in real life,” the researchers note. “This result confirms the important distinction between sexual fantasies and sexual wishes, which is usually stronger among women than among men.”

The researchers also found a number of write-in “favorite” sexual fantasies that were common among men had no equivalent in women’s fantasies. These included having sex with a trans woman (included in 4.2 percent of write-in fantasies), being on the receiving end of strap-on/non-homosexual anal sex (6.1 percent), and watching a partner have sex with another man (8.4 percent).

Next up, the researchers plan to map subgroups of sexual fantasies that often go together (for instance, those who reported submissive fantasies were also more likely to report domination fantasies, and both were associated with higher levels of overall sexual satisfaction). For now, they caution that “care should be taken before labeling (a sexual fantasy) as unusual, let alone deviant.”

It would be interesting to see the results of this study replicated in other areas — Quebec may or may not be representative of the rest of western society.

Update, 28 November: Maggie McNeill is not impressed by the study at all.

But there’s a bigger problem, which as it turns out I’ve written on before when the titillation du jour was the claim that fewer men were paying for sex:

    … the General Social Survey … has one huge, massive flaw that was mentioned by my psychology professors way back in the Dark Ages of the 1980s, yet seems not to trouble those who rely upon it so heavily these days: it is conducted in person, face to face with the respondents. And that means that on sensitive topics carrying criminal penalties or heavy social stigma, the results are less than solid; negative opinions of its dependability on such matters range from “unreliable” to “useless”. The fact of the matter is that human beings want to look good to authority figures (like sociologists in white lab coats) even when they don’t know them from Adam, so they tend to deviate from strict veracity toward whatever answer they think the interviewer wants to hear…

So, what does this study say constitutes an “abnormal” fantasy?

    “Clinically, we know what pathological sexual fantasies are: they involve non-consenting partners, they induce pain, or they are absolutely necessary in deriving satisfaction,” Christian Joyal, the lead author of the study, said…The researchers found that only two sexual fantasies were…rare: Sexual activities with a child or an animal…only nine sexual fantasies were considered unusual…[including] “golden showers,” cross-dressing, [and] sex with a prostitute…

Joyal’s claim that sadistic and rape fantasies are innately “pathological” is both insulting and totally wrong; we “know” no such thing. And did you think it was a coincidence that pedophilia and bestiality were the only two fantasies to fall into the “rare” category during a time when those are the two most vilified kinks in the catalog, kinks which will result in permanent consignment to pariah status if discovered? Guess again; as recently as the 1980s it was acceptable to at least talk about both of these, and neither is as rare as this “study” pretends. But Man is a social animal, and even if someone is absolutely certain of his anonymity (which in the post-Snowden era would be a much rarer thing than either of those fantasies), few are willing to risk the disapproval of a lab-coated authority figure even if he isn’t sitting directly in front of them. What this study shows is not how common these fantasies actually are, but rather how safe people feel admitting to them. And while that’s an interesting thing in itself, it isn’t what everyone from researchers to reporters to readers is pretending the study measured.

October 16, 2014

Italian recession officially ends, thanks to drugs and prostitution

Filed under: Economics,Europe — Tags: , , , , — Nicholas @ 10:21

As Kelly McParland put it, it’s “another reason to legalize everything nasty“:

Italy learnt it was no longer in a recession on Wednesday thanks to a change in data calculations across the European Union which includes illegal economic activities such as prostitution and drugs in the GDP measure.

Adding illegal revenue from hookers, narcotics and black market cigarettes and alcohol to the eurozone’s third-biggest economy boosted gross domestic product figures.

GDP rose slightly from a 0.1 percent decline for the first quarter to a flat reading, the national institute of statistics said.

Although ISTAT confirmed a 0.2 percent decline for the second quarter, the revision of the first quarter data meant Italy had escaped its third recession in the last six years.

The economy must contract for two consecutive quarters, from output in the previous quarter, for a country to be technically in recession.

It’s merely a change in the statistical measurement, not an actual increase in Italian economic activity. And, given that illegal revenue pretty much by definition isn’t (and can’t be) accurately tracked, it’s only an estimated value anyway.

October 15, 2014

The pay gap issue, again

Filed under: Business,Economics — Tags: , , , — Nicholas @ 09:28

There’s been a lot of moaning on about inequality recently — some are even predicting it will be the big issue in next year’s Canadian federal election — but the eye-popping figures being tossed around (CEOs being paid hundreds of times the average wage) are very much a case of statistical cherry-picking:

Before retiring to their districts for the fall, the House Democratic Caucus rallied behind the CEO/Employee Pay Fairness Act, which would prevent a public company from deducting executive compensation over $1 million unless it also gives rank-and-file employees raises that keep pace with the cost of living and labor productivity.

Meanwhile, the AFL-CIO and its aligned think tanks have made hay of the huge difference between the pay of CEOs and employees. One of the most widely cited measures of the “gap” comes from the AFL-CIO’s Executive Paywatch website.

  • The nation’s largest federation of unions laments that “corporate CEOs have been taking a greater share of the economic pie” while wages have stagnated for the rest of us.
  • As proof, it points to a 331-to-1 gap in compensation between America’s chief executives and the pay of the average worker.

That’s a sizable number. But don’t grab the pitchforks just yet, says Mark J. Perry, economic professor at the University of Michigan-Flint and resident scholar at the American Enterprise Institute, and Michael Saltsman, research director at the Employment Policies Institute.

The AFL-CIO calculated a pay gap based on a very small sample — 350 CEOs from the S&P 500. According to the Bureau of Labor Statistics, there were 248,760 chief executives in the U.S. in 2013.

  • The BLS reports that the average annual salary for these chief executives is $178,400, which we can compare to the $35,239-per-year salary the AFL-CIO uses for the average American worker.
  • That shrinks the executive pay gap from 331-to-1 down to a far less newsworthy number of roughly five-to-one.

October 13, 2014

Statistical sleight-of-hand on the dangers of texting while driving

Filed under: Health,Media,USA — Tags: , , , , — Nicholas @ 10:15

Philip N. Cohen casts a skeptical eye at the frequently cited statistic on the dangers of texting, especially to teenage drivers. It’s another “epidemic” of bad statistics and panic-mongering headlines:

Recently, [author and journalist Matt] Richtel tweeted a link to this old news article that claims texting causes more fatal accidents for teenagers than alcohol. The article says some researcher estimates “more than 3,000 annual teen deaths from texting,” but there is no reference to a study or any source for the data used to make the estimate. As I previously noted, that’s not plausible.

In fact, 2,823 teens teens died in motor vehicle accidents in 2012 (only 2,228 of whom were vehicle occupants). So, my math gets me 7.7 teens per day dying in motor vehicle accidents, regardless of the cause. I’m no Pulitzer Prize-winning New York Times journalist, but I reckon that makes this giant factoid on Richtel’s website wrong, which doesn’t bode well for the book.

In fact, I suspect the 11-per-day meme comes from Mother Jones (or whoever someone there got it from) doing the math wrong on that Newsday number of 3,000 per year and calling it “nearly a dozen” (3,000 is 8.2 per day). And if you Google around looking for this 11-per-day statistic, you find sites like textinganddrivingsafety.com, which, like Richtel does in his website video, attributes the statistic to the “Institute for Highway Safety.” I think they mean the Insurance Institute for Highway Safety, which is the source I used for the 2,823 number above. (The fact that he gets the name wrong suggests he got the statistic second-hand.) IIHS has an extensive page of facts on distracted driving, which doesn’t have any fact like this (they actually express skepticism about inflated claims of cell phone effects).

[…]

I generally oppose scare-mongering manipulations of data that take advantage of common ignorance. The people selling mobile-phone panic don’t dwell on the fact that the roads are getting safer and safer, and just let you go on assuming they’re getting more and more dangerous. I reviewed all that here, showing the increase in mobile phone subscriptions relative to the decline in traffic accidents, injuries, and deaths.

That doesn’t mean texting and driving isn’t dangerous. I’m sure it is. Cell phone bans may be a good idea, although the evidence that they save lives is mixed. But the overall situation is surely more complicated than the TEXTING-WHILE-DRIVING EPIDEMIC suggests. The whole story doesn’t seem right — how can phones be so dangerous, and growing more and more pervasive, while accidents and injuries fall? At the very least, a powerful part of the explanation is being left out. (I wonder if phones displace other distractions, like eating and putting on make-up; or if some people drive more cautiously while they’re using their phones, to compensate for their distraction; or if distracted phone users were simply the worst drivers already.)

October 8, 2014

Something is wrong when your “data adjustment” is to literally double the reported numbers

Filed under: Health,USA — Tags: , , — Nicholas @ 10:32

In Forbes, Trevor Butterworth looks at an odd data analysis piece where the “fix” for a discrepancy in reported drinks per capita is to just assume everyone under-reported and to double that number:

“Think you drink a lot? This chart will tell you.”

The chart, reproduced below breaks down the distribution of drinkers into deciles, and ends with the startling conclusion that 24 million American adults — 10 percent of the adult population over 18 — consume a staggering 74 drinks a week.

Time for a stiff drink infographic

The source for this figure is “Paying the Tab,” by Phillip J. Cook, which was published in 2007. If we look at the section where he arrives at this calculation, and go to the footnote, we find that he used data from 2001-2002 from NESARC, the National Institute on Alcohol Abuse and Alcoholism, which had a representative sample of 43,093 adults over the age of 18. But following this footnote, we find that Cook corrected these data for under-reporting by multiplying the number of drinks each respondent claimed they had drunk by 1.97 in order to comport with the previous year’s sales data for alcohol in the US. Why? It turns out that alcohol sales in the US in 2000 were double what NESARC’s respondents — a nationally representative sample, remember — claimed to have drunk.

While the mills of US dietary research rely on the great National Health and Nutrition Examination Survey to digest our diets and come up with numbers, we know, thanks to the recent work of Edward Archer, that recall-based survey data are highly unreliable: we misremember what we ate, we misjudge by how much; we lie. Were we to live on what we tell academics we eat, life for almost two thirds of Americans would be biologically implausible.

But Cook, who is trying to show that distribution is uneven, ends up trying to solve an apparent recall problem by creating an aggregate multiplier to plug the sales data gap. And the problem is that this requires us to believe that every drinker misremembered by a factor of almost two. This might not much of a stretch for moderate drinkers; but did everyone who drank, say, four or eight drinks per week systematically forget that they actually had eight or sixteen? That seems like a stretch.

We are also required to believe that just as those who drank consumed significantly more than they were willing to admit, those who claimed to be consistently teetotal never touched a drop. And, we must also forget that those who aren’t supposed to be drinking at all are also younger than 18, and their absence from Cook’s data may well constitute a greater error.

September 3, 2014

QotD: The relative size of the Chinese economy, historically speaking

Filed under: China,Economics,History,Quotations — Tags: , , — Nicholas @ 00:01

People seem to want to get freaked out about China passing the US in terms of the size of its economy. But in the history of Civilization there have probably been barely 200 years in the last 4000 that China hasn’t been the largest economy in the world. It probably only lost that title in the early 19th century and is just now getting it back. We are in some senses ending an unusual period, not starting one.

Warren Meyer, “It is Historically Unusual for China NOT to be the Largest Economy on Earth”, Coyote Blog, 2014-08-30.

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