Statistics for Astronomers XVII & Astroinformatics II
Virtual Summer Schools in Astrostatistics & Astroinformatics
hosted by Penn State’s Center for Astrostatistics
Penn State’s Summer School in Statistics for Astronomers provides astronomy graduate students and postdocs with a foundation in statistical inference and methodology. Topics include maximum likelihood and Bayesian modeling, nonparametrics, bootstrap resampling, regression and model selection, multivariate clustering and classification, spatial statistics, and time series analysis. Participants are trained in the powerful R statistical software environment.
The Astroinformatics Summer School helps astronomers incorporate modern statistical methods, machine learning techniques, and tools for harnessing big data into their research projects. Participants exercise the methods with astronomical datasets illustrating realistic challenges faced in contemporary research. Students are expected to arrive familiar with fundamentals of statistics at the level of the above Summer School.
Both programs will follow an enhanced virtual format combining live video lectures via Zoom, recorded video lectures, interactive computational notebook tutorials, live and asynchronous Q&A sessions with instructors. Slack channels address additional questions and support students with lab tutorials. The structure accommodates participants in different time zones. Participants can register for either program individually or both. Lectures and tutorials are presented by experienced educators in statistics and astrostatistics.
For more information and registration (contact address):
Astroinformatics: https://sites.psu.edu/astrostatistics/astroinfo-su22 (firstname.lastname@example.org)
Registration deadline: 27 May 2022
G. Jogesh Babu, Eric D. Feigelson, Eric B. Ford, Hyungsuk Tak -- Center for Astrostatistics, Penn State University