Abstract Details
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Activity Number:
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508
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Type:
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Invited
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Date/Time:
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Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #307406 |
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Title:
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Large-Scale Inference and Scientific Interpretability
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Author(s):
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Laura C. Lazzeroni*+
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Companies:
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Stanford University
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Keywords:
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genomics ;
p-values ;
GWAS ;
high-throughput
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Abstract:
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New technologies for measuring vast amounts of data have recently dominated the sciences, especially biology. The scale and precision of data have increased at an amazing rate, while time and cost per data point have decreased. Investigators have made less progress using large-scale data to reach reliable scientific conclusions or to achieve practical benefits for the general public, such as improved medical care. In this talk, I will discuss limitations of large-scale inference and statistical strategies for improving the interpretability and utility of its results.
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Authors who are presenting talks have a * after their name.
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