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'Feigelson and Babu, two of the leading figures in the new discipline of astrostatistics, have written a text that surely must be considered as the standard text on the subject. The book presents astronomers with an up-to-date overview of the foremost methods being used in astrostatistical analysis, providing numerous examples, as well as relevant R code, for how these methods can be used in their research. The text is useful to astronomers who are new to serious astrostatistical analysis, as well as to seasoned researchers.' Joseph M. Hilbe, Chair, ISI International Astrostatistics Network, Arizona State University/Jet Propulsion Laboratory 'This book covers in a single volume both the basic statistical material and more specialized material (clustering, classification, data mining, non-detections, time series analysis, and spatial point processes) that is essential for modern astronomers. 'The astronomical context' sections, which provide motivation for the ensuing statistical development, are particularly valuable ... The decision to use R to illustrate the ideas, methods, and tools, and to apply them to real astronomical data sets, will significantly enhance the value of the volume. The discipline of astrostatistics is experiencing a dramatic blossoming, and this book will provide the necessary vehicle for the new generation of astronomers.' David Hand, Imperial College London 'While many astrophysicists have deep training in statistical theory and great practical abilities, others have no or only elementary training in these areas, propagate old mistakes, and carry out sub-optimal data analysis. Modern Statistical Methods for Astronomy addresses this problem and will likely make a significant contribution. And just in time! The age of 'digital astronomy' - with its notoriously complex and huge data arrays - is already challenging our knowledge of advanced statistical methods and abilities to apply them in practice. Each chapter surveys statistical science relevant to a specific area in a way that should be easily comprehensible by all graduate and many undergraduate students, followed in most cases by selected applications in R. Serious readers of this text will be well-equipped to learn the most advanced techniques on their own.' Jeffrey D. Scargle, NASA Ames Research Center 'This one book is required reading as it tackles the often ignored need for profitability analysis in observational or measured data.' Spaceflight
