The methodology is straightforward. You take your subject and slide them into an fMRI machine, a humongous sleek, white ring, like a donut designed by Apple. Then you show the subject images of people engaging in social activities — shopping, talking, eating dinner. You flash 48 different photos in front of your subject's eyes, and ask them to figure out what emotions the people in the photos were probably feeling. All in all, it's a pretty basic neuroscience/psychology experiment. With one catch. The "subject" is a mature Atlantic salmon.
And it is dead.
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Genius science writer Ed Yong used to work for a cancer charity, so he's seen how the cancer research sausages get made. In a new post at Not Exactly Rocket Science, Ed takes you on a brief tour of the factory, explaining why even good data doesn't necessarily mean what you think it means.
The post is based around a new study that says 16.1% of all cancers worldwide are caused by infections. This statistic is talking about stuff like HPV—viruses and other infections that can prompt mutations in the cells they infect. Sometimes, those mutations propagate and become a tumor.
That statistic tells us that infections play a role in more cancers than most laypeople probably think, Ed says. It gives us an idea of the scale of the problem. But you have to be careful not to read too much into that 16.1%.
The latest paper tells us that 16.1% of cancers are attributable to infections. In 2006, a similar analysis concluded that 17.8% of cancers are attributable to infections. And in 1997, yet another study put the figure at 15.6%. If you didn’t know how the numbers were derived, you might think: Aha! A trend! The number of infection-related cancers was on the rise but then it went down again.
That’s wrong. All these studies relied on slightly different methods and different sets of data. The fact that the numbers vary tells us nothing about whether the problem of infection-related cancers has got ‘better’ or ‘worse’. (In this case, the estimates are actually pretty close, which is reassuring. I have seen ones that vary more wildly. Try looking for the number of cancers caused by alcohol or poor diets, if you want some examples).
And that's only one of the complications involved in understanding cancer statistics. You really should read Ed's entire post. After you do, a lot of apparent inconsistencies in cancer data will make a lot more sense to you. For instance: What about the cancers caused by radiation exposure?
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Between now and 2020, the greatest increases in population growth in the United States are projected to happen in the places that have the biggest problems with fresh water availability
. This isn't just a drinking water problem, or even an agriculture problem. It's an energy issue, too. Most of our electricity is made by finding various ways to boil water, producing steam that turns a turbine in an electric generator. In 2000, we used as much fresh water to produce electricity as we used for irrigation—each sector represented 39% of our total water use. (From a poster at Lawrence Berkeley National Laboratory.) — Maggie
Bruce Schneier comments on an NYT report on cybercrime that shows that there's just not much money to be had in being a ripoff artist. Dinei Florêncio and Cormac Herley wrote:
A cybercrime where profits are slim and competition is ruthless also offers simple explanations of facts that are otherwise puzzling. Credentials and stolen credit-card numbers are offered for sale at pennies on the dollar for the simple reason that they are hard to monetize. Cybercrime billionaires are hard to locate because there aren’t any. Few people know anyone who has lost substantial money because victims are far rarer than the exaggerated estimates would imply.
The authors frame cybercrime as a "tragedy of the commons," where the overfishing (overphishing) by crooks has reduced everyone's margins to nothing, making it hard graft indeed. Meanwhile, cybercrime estimates are subject to the same lobbynomics used to calculate losses from music downloading and profits from drug seizures:
Suppose we asked 5,000 people to report their cybercrime losses, which we will then extrapolate over a population of 200 million. Every dollar claimed gets multiplied by 40,000. A single individual who falsely claims $25,000 in losses adds a spurious $1 billion to the estimate. And since no one can claim negative losses, the error can't be canceled.
Cybercrime as a Tragedy of the Commons
In The Atlantic, Alexander Furnas debunks the DHS's proposal for a "precrime" screening system that will attempt to predict which passengers are likely to commit crimes, and single those people out for additional screening. FAST (Future Attribute Screening Technology) "will remotely monitor physiological and behavioral cues, like elevated heart rate, eye movement, body temperature, facial patterns, and body language, and analyze these cues algorithmically for statistical aberrance in an attempt to identify people with nefarious intentions." They'll build the biometric "bad intentions" profile by asking experimental subjects to carry out bad deeds and monitoring their vital signs. It's a mess, scientifically, and it will falsely accuse millions of innocent people of planning terrorist attacks.
First, predictive software of this kind is undermined by a simple statistical problem known as the false-positive paradox. Any system designed to spot terrorists before they commit an act of terrorism is, necessarily, looking for a needle in a haystack. As the adage would suggest, it turns out that this is an incredibly difficult thing to do. Here is why: let's assume for a moment that 1 in 1,000,000 people is a terrorist about to commit a crime. Terrorists are actually probably much much more rare, or we would have a whole lot more acts of terrorism, given the daily throughput of the global transportation system. Now lets imagine the FAST algorithm correctly classifies 99.99 percent of observations -- an incredibly high rate of accuracy for any big data-based predictive model. Even with this unbelievable level of accuracy, the system would still falsely accuse 99 people of being terrorists for every one terrorist it finds. Given that none of these people would have actually committed a terrorist act yet distinguishing the innocent false positives from the guilty might be a non-trivial, and invasive task.
Of course FAST has nowhere near a 99.99 percent accuracy rate. I imagine much of the work being done here is classified, but a writeup in Nature reported that the first round of field tests had a 70 percent accuracy rate. From the available material it is difficult to determine exactly what this number means. There are a couple of ways to interpret this, since both the write-up and the DHS documentation (all pdfs) are unclear. This might mean that the current iteration of FAST correctly classifies 70 percent of people it observes -- which would produce false positives at an abysmal rate, given the rarity of terrorists in the population. The other way of interpreting this reported result is that FAST will call a terrorist a terrorist 70 percent of the time. This second option tells us nothing about the rate of false positives, but it would likely be quite high. In either case, it is likely that the false-positive paradox would be in full force for FAST, ensuring that any real terrorists identified are lost in a sea of falsely accused innocents.
Homeland Security's 'Pre-Crime' Screening Will Never Work
(Image: Brockhaus and Efron Encyclopedic Dictionary, a Creative Commons Attribution (2.0) image from double-m2's photostream)
Here's a clip of a Danish TV show discussing ACTA, which Denmark has fiercely advocated in favor of. It starts with the head of a rightsholder society and the Danish trade minister quoting dodgy statistics about the extent and cost of piracy, and then demonstrates that these statistics are patently false, and finally, brings out those responsible for quoting them and gets them to admit their errors. Priceless.
You can see both the Danish Trade Minister and the head of a Danish music rights organization (and famous Danish musician) Ivan Pedersen appear on a TV show below (with English subtitles). On the show, a well-informed presenter focuses on how both of these ACTA defenders claimed that 95% of music downloaded in Denmark was unauthorized, and carefully shows how that's simply false -- and then gets both of the ACTA defenders to admit that the numbers were wrong.
Danish Trade Minister Apologizes For Using Bogus Industry Numbers To Support Pro-ACTA Argument
The NYT's Andrew Ross Sorkin quotes Barry Ritholtz's digging into how Facebook's IPO documents define "active" users and finds that many of them may never visit the site. Facebook counts you as "active" if your only involvement with the service is setting it up to republish your Twitter feed, or if you click "Like" buttons but never log in to the actual service. This should matter to investors, since Facebook earns no advertising revenue from those users, though it may earn some other income by reselling the private details of their browsing habits as gleaned from its tracking cookies.
In other words, every time you press the “Like” button on NFL.com, for example, you’re an “active user” of Facebook. Perhaps you share a Twitter message on your Facebook account? That would make you an active Facebook user, too. Have you ever shared music on Spotify with a friend? You’re an active Facebook user. If you’ve logged into Huffington Post using your Facebook account and left a comment on the site — and your comment was automatically shared on Facebook — you, too, are an “active user” even though you’ve never actually spent any time on facebook.com.
“Think of what this means in terms of monetizing their ‘daily users,’ ” Barry Ritholtz, the chief executive and director for equity research for Fusion IQ, wrote on his blog. “If they click a ‘like’ button but do not go to Facebook that day, they cannot be marketed to, they do not see any advertising, they cannot be sold any goods or services. All they did was take advantage of FB’s extensive infrastructure to tell their FB friends (who may or may not see what they did) that they liked something online. Period.”
Those Millions on Facebook? Some May Not Actually Visit
(via Memex 1.1)
The Centers for Disease Control and Prevention, and the World Health Organization, say that H5N1 bird flu kills some 60% of the human beings it manages to infect. Basically, it hasn't infected many people—because it can't be spread from person to person—but most of the people it does infect die.
But this might not be the full story.
After I posted a summary of the current controversies surrounding H5N1 research, I got an interesting email from Vincent Racaniello, a professor of microbiology at Columbia University Medical Center. Racaniello points out that the 60% death rate statistics are based on people who show up at hospitals with serious symptoms of infection. So far, there've only been about 600 cases. And, yes, about 60% of them have died.
However, they don't necessarily represent everybody who has contracted H5N1.
A death rate is only as good as statistics on the rate of infection. If you've got an inaccurate count of the number of people infected, your death rate is going to be wrong. And there's some evidence that might be the case with H5N1.
In a recent study of rural Thai villagers, sera from 800 individuals were collected and analyzed for antibodies against several avian influenza viruses, including H5N1, by hemagglutination-inhibition and neutralization assays. The results indicate that 73 participants (9.1%) had antibody titers against one of two different H5N1 strains. The authors conclude that ‘people in rural central Thailand may have experienced subclinical avian influenza virus infections’. A subclinical infection is one without apparent signs of illness.
If 9% of the rural Asian population has been subclinically infected with avian H5N1 influenza virus strains, it would dramatically change our view of the pathogenicity of the virus. Extensive serological studies must be done to determine the extent of human infection with avian H5N1 influenza viruses. Until we know how many individuals are infected with avian influenza H5N1, we must refrain from making dire conclusions about the pathogenicity of the virus.
Even with all those Snowpocalypseses(?), NASA says that 2011 was still the ninth warmest year on record since 1880—and all but one of the top 10 warmest years have happened in the last 11 years. 1998 is third-hottest
, although it's worth noting that the top six years are all close enough that they may as well be fundamentally tied for first
. — Maggie
At Bloomberg Business Week, Vali Chandrasekaran makes me incredibly happy by creating a series of six infographics demonstrating the ridiculous connections you can make when you start confusing correlation and causation. Did a conspiracy of baby Avas cause the U.S. housing market to implode? Was Michele Bachmann's candidacy doomed by the end of Staten Island Cakes? Are scientists raising the global average temperature in order to increase their own research funding? Find out here!
Biostatistics Ryan Gosling will look deeply into your eyes and ask about your p-value.
Via Jacquelyn Gill
What are the odds that you, as an individual, exist? Pretty good, you'd guess, since you're sitting right here reading this. But, in an abstract sense, the chances that you exist are really rather slim. In fact, once you see the full infographic, put together by futurist and designer Sofya Yampolsky of Visual.ly, I'm sure you'll be much more skeptical of your existence.
The infographic is based on this post by Dr. Ali Binazir.
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A retired climate research satellite will plummet to Earth on Friday
. There is a 1-in-3,200 chance of it hitting a person. BUT! Don't worry too much about that, says Scientific American reporter John Matson
. A 1-in-3200 chance of a piece of the satellite hitting somebody
, is not the same as a 1-in-3200 chance of it hitting you, specifically. He calculates the risk of that as 1-in-22 trillion
A press release from a mysterious "independent" Australian research outfit announced that if Aussie ISPs would help the movie industry by threatening the families that Hollywood says are downloading without permission, copyright infringement would fall by a whopping 72 percent
This is a big number. A very big number. Especially since the same poll question, when asked in France (where the motion picture lobby has succeeded in passing a "disconnect anyone we don't like from the Internet" law) showed that only four percent of downloaders changed their habits out of fear of detection.
No, it's not that Australians are easily frightened. Rather, the Intellectual Property Awareness Foundation (an "independent" firm that lists the MPAA on its board and has no visible clients apart from the entertainment industry) included responses from people who don't download in its poll -- that is, they lumped in the very small number of people (zero, possibly) who said, "I download, and this would make me stop" with the very large number of people who said, "I don't download, but, well, hypothetically, if I did, this might make me stop."
If 72 percent say they would stop sharing after a warning, then 28 percent didn’t agree with this statement. And since only 22 percent of the people said they used file-sharing software in 2011 (the only people who would be affected by a three strikes system), this means that warnings from ISPs wouldn’t even deter people who aren’t the target of this system in the first place.
Anti-Piracy Lobby Misleads Aussie Press for Three-Strikes Campaign
Or put differently, it could very well be that none of the 22 percent file-sharers indicated that they would stop doing so when notified by their ISP.
Now that’s an entirely different conclusion isn’t it?
A great example of why details and context always, always matter, from the surgeon/blogger at The Skeptical Scalpel:
Twelve patients who served as their own controls wore compression stockings for a week and then no stockings for a week alternating. The stockings lowered the amount of fluid in the neck by 60%, a statistically significant difference. So far, so good.
This resulted in another highly statistically significant finding, which was a 36% reduction in episodes of apnea [cessation of breathing] and hypopnea [inadequate breathing]. Sounds good, right? The problem is that the average number of episodes of apnea/hypopnea decreased from 48 per hour to 31 per hour. Patients experiencing more than 30 episodes of apnea/hypopnea per hour are classified as having severe obstructive sleep apnea. This means that the treatment only put the patients in the low range of severe obstructive sleep apnea. They still would require maximum therapy.
Via Ivan Oransky