%0 Book %A Ivezić, Željko, yazar %E Connolly, Andrew %E Vanderplas, Jacob T. %E Gray, Alexander, %I Princeton University Press %D 2014 %C Princeton, N.J. %G English %B Princeton series in modern observational astronomy %@ 9781400848911 %@ 1400848911 %@ 0691151687 %@ 9780691151687 %@ 9781306373845 %@ 1306373840 %T Statistics, data mining, and machine learning in astronomy : a practical Python guide for the analysis of survey data %X As telescopes, detectors, and computers grow ever more powerful, the volume of data at the disposal of astronomers and astrophysicists will enter the petabyte domain, providing accurate measurements for billions of celestial objects. This book provides a comprehensive and accessible introduction to the cutting-edge statistical methods needed to efficiently analyze complex data sets from astronomical surveys such as the Panoramic Survey Telescope and Rapid Response System, the Dark Energy Survey, and the upcoming Large Synoptic Survey Telescope. It serves as a practical handbook for graduate students and advanced undergraduates in physics and astronomy, and as an indespensable reference for researchers