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science.article - Science 19 November 1999: Vol. 286. no....

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Science 19 November 1999: Vol. 286. no. 5444, pp. 1460 - 1464 DOI: 10.1126/science.286.5444.1460 Prev | Table of Contents | Next NEWS FOCUS STATISTICS: Bayes Offers a 'New' Way to Make Sense of Numbers David Malakoff A 236-year-old approach to statistics is making a comeback, as its ability to factor in hunches as well as hard data finds applications from pharmaceuticals to fisheries After 15 years, environmental researcher Kenneth Reckhow can still feel the sting of rejection. As a young scientist appearing before an Environmental Protection Agency review panel, Reckhow was eager to discuss his idea for using an unorthodox statistical approach in a water-quality study. But before he could say a word, an influential member of the panel unleashed a rhetorical attack that stopped him cold. "As far as he was concerned, I was a Bayesian, and Bayesian statistics were worthless," recalls Reckhow, now at Duke University in Durham, North Carolina. "The idea was dead before I even got to speak." Reckhow is no longer an academic outcast. And the statistical approach he favors, named after an 18th century Presbyterian minister, Thomas Bayes, now receives a much warmer reception from the scientific establishment. Indeed, Bayesian statistics, which allows researchers to use everything from hunches to hard data to compute the probability that a hypothesis is correct, is experiencing a renaissance in fields of science ranging from astrophysics to genomics and in real-world applications such as testing new drugs and setting catch limits for fish. The long-dead minister is also weighing in on lawsuits and public policy decisions (see p. 1462 ), and is even making an appearance in consumer products. It is his ghost, for instance, that animates the perky paperclip that pops up on the screens of computers running Microsoft Office software, making Bayesian guesses about what advice the user might need. "We're in the midst of a Bayesian boom," says statistician John Geweke of the University of Iowa, Iowa City. Advances in computers and the limitations of traditional statistical methods are part of the reason for the new popularity of this old approach. But researchers say the Bayesian
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approach is also appealing because it allows them to factor expertise and prior knowledge into their computations--something that traditional methods frown upon. In addition, advocates say it produces answers that are easier to understand and forces users to be explicit about biases obscured by reigning "frequentist" approaches. To be sure, Bayesian proponents say the approach is no panacea--and the technique has detractors. Some researchers fear that because Bayesian analysis can take into account prior opinion, it could spawn less objective evaluations of experimental results. "The problem is that prior beliefs can be just plain wrong" or difficult to quantify properly, says statistician Lloyd Fisher of the University of Washington, Seattle. Physicians enthusiastic about a particular treatment, for instance, could subtly sway trial results in their favor. Even some advocates
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science.article - Science 19 November 1999: Vol. 286. no....

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