Abstract Details
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Activity Number:
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577
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Type:
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Invited
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Date/Time:
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Thursday, August 7, 2014 : 8:30 AM to 10:20 AM
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Sponsor:
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ASA
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Abstract #314119
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Title:
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A Framework for Statistical Inference in Astronomy
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Author(s):
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Chad Schafer*+
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Companies:
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Carnegie Mellon
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Keywords:
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Abstract:
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The rapid growth of astronomical data sets, coupled with the complexity of the questions scientists seek to answer with these data, creates an increasing need for the utilization of advanced statistical inference methods in astrophysics. In this talk focus is placed on situations where the underlying objective is the estimation of cosmological parameters, the key physical constants that characterize the Universe. This broad inference goal is best divided into three stages due to the complex relationship between these parameters and the observable data. The objectives of this talk are to explain important aspects of the astronomical background and describe these stages to astrophysical inference.
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Authors who are presenting talks have a * after their name.
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