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Summer School in Statistics for Astronomers X (June 2-6, 2014)
Statistical Modeling of Cosmic Populations (June 9-10, 2014)
Bayesian Computing for Astronomical Data Analysis (June 11-13, 2014)

Registration Deadline: May 5, 2014 or earlier if the enrollment limit reaches.

Astronomy at the beginning of the 21st century, and particularly research arising from wide-field survey observatories at various wavebands, finds itself with serious challenges in statistical treatments of data to achieve its astrophysical goals. A vast range of statistical problems arise in the scientific interpretation of astronomical studies involving sampling, multivariate and survival analysis, image and spatial analysis, signal processing and time series analysis, nonlinear regression, and more.

It is this diversity of statistical issues confronting astronomy today that led to the creation of the Center for Astrostatistics at Penn State in 2003 to facilitate development and promulgation of statistical expertise and toolkits for astronomy and related observational sciences. The Center is housed in the Department of Statistics. The activities of the Center are multi-faceted: conduct and support research on forefront problems; provide forums where active astrostatistical researchers can interact; foster new cross-disciplinary collaborations; liaise with other organizations oriented towards statistical applications in physical sciences. One of the aims is to disseminate advanced methodologies to the wider astronomical and space science communities through curriculum development, tutorial workshops, Web-based resources, and public software.

VOStat is a web based service providing a suite of tools allowing astronomers to use both simple and sophisticated statistical routines. StatCodes is a Web metasite with links to public domain software implementing statistical methods.

The Center serves as a crossroads where researchers at the interfaces between statistics, data analysis, astronomy, space and observational physics collaborate, develop and share methodologies, and together prepare the next generation of researchers.

  MSMA

Modern Statistical Methods for Astronomy
With R Applications

Eric D. Feigelson;   G. Jogesh Babu
Cambridge University Press (2012)

Datasets, R scripts, a discount form, and other details can be found here.

Won the 2012 Association of American Publishers PROSE Award in the Cosmology and Astronomy section.

Past Programs


NSFDepartment of StatisticsEberly College of ScienceDepartment of Astronomy and Astrophysics