Summer School in Statistics for Astronomers & Physicists (June 5-17, 2005)

Overview:   The volume and complexity of data in astronomy and physics have increased enormously in recent years. Statistics provides the means for extracting physical insights from such data. The Center for Astrostatistics (CASt) at Penn State is organizing a series of summer school sessions to train astronomers and physicists in advanced statistical methods for handling a diversity of statistical issues confronting astronomy, space sciences, and high energy particle physics. The instruction will be interspersed with Practicum sessions in which participants will obtain hands-on experience in the computer-based analysis of astronomical data sets using public domain software and algorithms studied in the instructional sessions.

The 2005 summer school offering has three sessions. Participants may register for one session or any combination of sessions. Enrollment is limited to 25 participants per session. Local accommodation is provided at no cost to the admitted participants during the sessions.

• Statistical inference for astronomers  (June 5-10, 2005)
  A 5-day course in fundamental statistical inference designed to provide physical scientists, with little or no prior exposure to statistics, with a strong conceptual foundation in modern statistics and to develop a repertoire of well-established techniques applicable to observational astronomy and physics. These statistical techniques include hypothesis testing and parameter estimation, recent developments in confidence interval estimation, non-parametric methods, maximum likelihood methods, Monte Carlo methods, and many other procedures.  

• Spatial processes and image analysis  (June 12-14, 2005)
  A 3-day specialized course in image analysis, wavelets and spatial point processes. Developing sophisticated tools for image restoration and noise reduction, feature extraction, and characterization of spatial processes such as the clustering of galaxies in 3-dimensional redshift space or Galactic stars in 6-dimensional phase space. 

• Computational algorithms for astrostatistics  (June 15-17, 2005)
  A 3-day specialized course in computational algorithms which provide insights into problems inaccessible by standard analytic approaches. These methods include EM-algorithms, Markov chain Monte Carlo algorithms, genetic and evolutionary algorithms, and homotopy continuation methods. The course emphasize methods for constructing confidence intervals for nested models, high-dimensional nonlinear relationships, summations needed for Bayesian approaches, general formulation of EM algorithms, convergence properties, and computation of standard errors.  
  

In the spring of 2006 and summer of 2007, CASt plans to offer courses in Bayesian inference, multivariate analysis, and time series analysis.

Forthcoming 2006 Penn State Conference:

Statistical Challenges in Modern Astronomy IV. The fourth in a series of interdisciplinary international conferences, Statistical Challenges in Modern Astronomy, will be held during June 12-15, 2006 at the Pennsylvania State University, University Park, USA.