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\centerline{\bf STANFORD UNIVERSITY}
\centerline{\bf DEPARTMENT OF STATISTICS}
\centerline{\big DEPARTMENT SEMINAR}
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\centerline{4:15 p.m., Tuesday, March 19, 2002}
\centerline{Sequoia Hall Room 200}
\centerline{(Cookies at 3:45 in 1st Floor Lounge)}

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\centerline{\sl Jeffrey D. Scargle}
\centerline{\sl Space Science Division}
\centerline{\sl NASA Ames Research Center}
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\centerline{\bf The New Astronomy: Understanding the Universe through Statistics}
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Many exciting scientific discoveries are emerging from data flowing
out of ground- and space-based astronomical observatories.
The corresponding statistics challenges have led to a growing need
for automated analysis and discovery techniques.  I will describe
new tools that may be useful in this context, including methods to:

  * detect local structure in noisy Gamma-ray time series
  * estimate the spatial power spectrum of Cosmic Background Radiation
  * construct bin-free histograms of Solar neutrino data
  * detect and characterize clusters of galaxies
  * mine high-dimensional multi-parameter data spaces

I will also discuss concepts related to what John McCarthy calls
Phenomenal Data Mining, and describe a new opportunity for
Stanford/Ames research collaborations.


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