In the past two years, the environment within which astronomers conduct their data analysis and management has rapidly changed. Working Groups associated with international societies and Big Data projects have emerged to support and stimulate the new
fields of astroinformatics and astrostatistics. Sponsoring societies include the Intenational Statistical Institute, International Astronomical Union, American Astronomical Society, and Large Synoptic Survey Telescope project. They enthusiastically support cross-disciplinary activities where the advanced capabilities of computer science, statistics and related fields of applied mathematics are applied to advance research on planets, stars, galaxies and the Universe. The ADASS community is encouraged to join these organizations and to explore and engage in their public communication Web site, the Astrostatistics and Astroinformatics Portal (http://asaip.psu.edu).
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statist
ical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied statistics relevant to astronomical research are briefly discussed: nonparametric methods for use when little is known about the behavior of the astronomical populations or processes; data smoothing with kernel density estimation and nonparametric regression; unsupervised clustering and supervised classification procedures for multivariate problems; survival analysis for astronomical datasets with nondetections; time- and frequency-domain times series analysis for light curves; and spatial statistics to interpret the spatial distributions of points in low dimensions. Two types of resources are presented: about 40 recommended texts and monographs in various fields of statistics, and the public domain R software system for statistical analysis. Together with its sim 3500 (and growing) add-on CRAN packages, R implements a vast range of statistical procedures in a coherent high-level language with advanced graphics.
Most stars are born in rich young stellar clusters (YSCs) embedded in giant molecular clouds. The most massive stars live out their short lives there, profoundly influencing their natal environments by ionizing HII regions, inflating wind-blown bubbl
es, and soon exploding as supernovae. Thousands of lower-mass pre-main sequence stars accompany the massive stars, and the expanding HII regions paradoxically trigger new star formation as they destroy their natal clouds. While this schematic picture is established, our understanding of the complex astrophysical processes involved in clustered star formation have only just begun to be elucidated. The technologies are challenging, requiring both high spatial resolution and wide fields at wavelengths that penetrate obscuring molecular material and remove contaminating Galactic field stars. We outline several important projects for the coming decade: the IMFs and structures of YSCs; triggered star formation around YSC; the fate of OB winds; the stellar populations of Infrared Dark Clouds; the most massive star clusters in the Galaxy; tracing star formation throughout the Galactic Disk; the Galactic Center region and YSCs in the Magellanic Clouds. Programmatic recommendations include: developing a 30m-class adaptive optics infrared telescope; support for high-resolution and wide field X-ray telescopes; large-aperture sub-millimeter and far-infrared telescopes; multi-object infrared spectrographs; and both numerical and analytical theory.
