The AstroStat Slog

R is a programming language and software for statistical computing and graphics. It is the most popular tool for statisticians and a widely used software for statistical data analysis thanks to the fact that its source code is freely available and it is fairly easy to access from installation to theoretical application.

Most of information about R can be found at R Project including the software itself and many add-on packages. These individually contributed packages serve particular statistical interests of their users. The documentation menu on the website and each packages contain extensive documentations of how-to’s. Some large packages include demos so that following the scripts in a demo makes R learning easy.
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The Statistics Jargon for Astronomers has revived (Jan. 2007) but now, it is barely breathing. Effortlessly search engines and Internet encyclopedia provide details on statistical terminologies for astronomers, which cast the largest difficulty on this jargon website. We urge both astronomers and statisticians’ contributions for compiling this lexicon and their discussions on both subjects.

In Spring 2006, SAMSI (Statistical and Applied Mathematical Sciences Institute) program on Astrostatistics began with tutorials, followed by workshops and regular meetings of working groups (Exoplanets, Surveys and Population Studies, Gravitational Lensing, Source Detection and Feature Detection, Particle Physics). Workshop speakers/participants and working group members brought up many statistical challenges in astronomy and physics and had extensive discussions. Summaries and relevant materials are available from the websites (click the links; some materials such as journal papers are password protected).

Since Summer 2005, G. Jogesh Babu (Statistics) and Eric Feigelson (Astronomy) have organized lectures and lab sessions on statistics for astronomers and physicists. Lecturers are professors from Penn State statistics department and invited renown scientists from different countries. Students show diverse demography as well. Within a week or so, students listen Statistics 101 to recently published statistical theories particularly applied to astronomical data. They also learn how to use R, a statistical software and script language to perform statistics they learn through lectures. Past two years, this summer school proved its uniqueness and usefulness. More information on the upcoming school can be found at http://astrostatistics.psu.edu/su07/index.html and other topics regarding astrostatistics at Center for AstroStatistics at Penn State.

Generally, astronomical data archives are open to public. Also, astronomy has been the leading force of developing software and hardware to handle massive data, which nowadays receive spotlights from statistics. Although the astronomical data look easy to be accessed for some statistical challenges, compared to data sets of other disciplines, statistical applications on astronomical data are unlikely to be found. What is the cause of this long engagement period?
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Both in astronomy and statistics, python is recognized as a versatile programming language. I asked python tutorials to Alanna. The following is her answer, which looks very useful for those who wish to learn python.
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