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This is the largest nationally representative study to date of the toll taken by sepsis and pneumonia, two conditions often caused by deadly microbes, including the antibiotic-resistant bacteria MRSA. Such infections can lead to longer hospital stays, serious complications and even death. "In many cases, these conditions could have been avoided with better infection control in hospitals," said Ramanan Laxminarayan, Ph.D., principal investigator for Extending the Cure, a project examining antibiotic resistance based at the Washington, D.C. think-tank Resources for the Future. "Infections that are acquired during the course of a hospital stay cost the United States a staggering amount in terms of lives lost and health care costs," he said. "Hospitals and other health care providers must act now to protect patients from this growing menace." Laxminarayan and his colleagues analyzed 69 million discharge records from hospitals in 40 states and identified two conditions caused by health care-associated infections: sepsis, a potentially lethal systemic response to infection and pneumonia, an infection of the lungs and respiratory tract. The researchers looked at infections that developed after hospitalization. They zeroed in on infections that are often preventable, like a serious bloodstream infection that occurs because of a lapse in sterile technique during surgery, and discovered that the cost of such infections can be quite high: For example, people who developed sepsis after surgery stayed in the hospital 11 days longer and the infections cost an extra $33,000 to treat per person. Even worse, the team found that nearly 20 percent of people who developed sepsis after surgery died as a result of the infection. "That's the tragedy of such cases," said Anup Malani, a study co-author, investigator at Extending the Cure, and professor at the University of Chicago. "In some cases, relatively healthy people check into the hospital for routine surgery. They develop sepsis because of a lapse in infection control—and they can die." The team also looked at pneumonia, an infection that can set in if a disease-causing microbe gets into the lungs—in some cases when a dirty ventilator tube is used. They found that people who developed pneumonia after surgery, which is also thought to be preventable, stayed in the hospital an extra 14 days. Such cases cost an extra $46,000 per person to treat. In 11 percent of the cases, the patient died as a result of the pneumonia infection.

Statistical validation of results, as Shaffer described it, simply involves testing the null hypothesis: that the pattern you detect in your data occurs at random. If you can reject the null hypothesis—and science and medicine have settled on rejecting it when there's only a five percent or less chance that it occurred at random—then you accept that your actual finding is significant. The problem now is that we're rapidly expanding our ability to do tests. Various speakers pointed to data sources as diverse as gene expression chips and the Sloan Digital Sky Survey, which provide tens of thousands of individual data points to analyze. At the same time, the growth of computing power has meant that we can ask many questions of these large data sets at once, and each one of these tests increases the prospects than an error will occur in a study; as Shaffer put it, "every decision increases your error prospects." She pointed out that dividing data into subgroups, which can often identify susceptible subpopulations, is also a decision, and increases the chances of a spurious error. Smaller populations are also more prone to random associations. In the end, Young noted, by the time you reach 61 tests, there's a 95 percent chance that you'll get a significant result at random. And, let's face it—researchers want to see a significant result, so there's a strong, unintentional bias towards trying different tests until something pops out. Young went on to describe a study, published in JAMA, that was a multiple testing train wreck: exposures to 275 chemicals were considered, 32 health outcomes were tracked, and 10 demographic variables were used as controls. That was about 8,800 different tests, and as many as 9 million ways of looking at the data once the demographics were considered.

Trade's effect on military conflict is one of the most important issues in international relations. The last decade has seen research and debate into the role of trade intensify; Liberals argue that trade brings peace, neo-realists and neo-Marxists reason that trade brings conflict, and classical realists contend that trade has no impact. This debate is not just academic: some key U.S. policymakers (Senator McCain and former President Clinton for instance) believe that trade brings peace, a view that contributes to their support for free trade. Economists developed bilateral trade models in isolation from models of interstate conflict, which were the work of political scientists. These two types of models handle distance between nations differently. Bilateral trade takes its cue from Isaac Newton's formula for the gravitational attraction between two objects: the larger the objects' masses and the shorter the distance between them, the larger the attraction. So the larger the trade partners' economies and the closer they are to one another, the greater their trade. However, conflict models instead incorporate shared borders by land or close distance over water (contiguity) - stressing the role of border disputes in sparking interstate conflict. Distance is included in conflict equations based on the idea that an army gets weaker the farther it strays from its base, but what point in a nation to pick for the trade and conflict equation is unclear. Often theorists use the distance between capital cities, which is problematic: wars generally happen around borders where armies are often based, and capitals have historically changed without this altering the likelihood of war between the nation and its neighbours. The authors suggest that the trade data set plugged into trade and conflict equations is critical. This type of data often contains gaps - there are a number of reasons why data from a particular nation might be unavailable, inevitably leaving researchers to make assumptions. The majority of trade and conflict studies define conflict to include all types of militarised interstate disputes (MIDs). But Keshk, Reuveny, and Pollins question the results generated when different conflict definitions are chosen. For instance, a conflict such as a threat to use nuclear weapons would not cause fatalities, but may still have some impact on trade and vice versa. In fact, by altering the data treatment and assumptions in the equation, the authors generated a variety of results, which supported several different theoretical viewpoints. The authors suggest that future research should investigate questions of missing bilateral trade data, and attempt a more subtle use of the meaning of "military conflict". Researchers might also develop distance and contiguity measures at a more sophisticated level. "Any signal that trade brings peace remains weak and inconsistent, regardless of the way proximity is modelled in the conflict equation. The signal that conflict reduces trade, in contrast, is strong and consistent," say the authors. "Any study of the effect of trade on conflict that ignores the reverse fact is practically guaranteed to produce estimates that contain simultaneity bias." Studies of the relationship between international trade and military conflict can be traced back many centuries, particularly in the works of luminaries such as de Montesquieu, Immanuel Kant, John Hobson, Vladimir Lenin, Henry Morgenthau, Kenneth Waltz, Frederic List, and Albert Hirschman. This latest study emphasises that international politics are affecting trade between nation pairs, while it is far less obvious whether trade systematically affects politics. "To our colleagues from the liberal camp we would like to say that we still believe there are limited circumstances in which more trade may help lead countries to more peaceful resolutions of their differences, particularly if they are already at peace," the authors state. "However, it is past time for academics and policymakers to look beyond the naive claim that the cultivation of trade ties will always and everywhere produce a more peaceful world."

"People tend to conform their factual beliefs to ones that are consistent with their cultural outlook, their world view," Braman says. The Cultural Cognition Project has conducted several experiments to back that up. Participants in these experiments are asked to describe their cultural beliefs. Some embrace new technology, authority and free enterprise. They are labeled the "individualistic" group. Others are suspicious of authority or of commerce and industry. Braman calls them "communitarians." In one experiment, Braman queried these subjects about something unfamiliar to them: nanotechnology — new research into tiny, molecule-sized objects that could lead to novel products. "These two groups start to polarize as soon as you start to describe some of the potential benefits and harms," Braman says. The individualists tended to like nanotechnology. The communitarians generally viewed it as dangerous. Both groups made their decisions based on the same information. "It doesn't matter whether you show them negative or positive information, they reject the information that is contrary to what they would like to believe, and they glom onto the positive information," Braman says.

"Basically the reason that people react in a close-minded way to information is that the implications of it threaten their values," says Dan Kahan, a law professor at Yale University and a member of The Cultural Cognition Project. Kahan says people test new information against their preexisting view of how the world should work. "If the implication, the outcome, can affirm your values, you think about it in a much more open-minded way," he says. And if the information doesn't, you tend to reject it. In another experiment, people read a United Nations study about the dangers of global warming. Then the researchers told the participants that the solution to global warming is to regulate industrial pollution. Many in the individualistic group then rejected the climate science. But when more nuclear power was offered as the solution, says Braman, "they said, you know, it turns out global warming is a serious problem."And for the communitarians, climate danger seemed less serious if the only solution was more nuclear power.