The Internet contains so much information and data for astronomers that just finding what you want is a daunting task, and downloading can take hours of computer and telephone time.

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 indispensable reference for researchers. Statistics, Data Mining, and Machine Learning in Astronomy presents a wealth of practical analysis problems, evaluates techniques for solving them, and explains how to use various approaches for different types and sizes of data sets. For all applications described in the book, Python code and example data sets are provided. The supporting data sets have been carefully selected from contemporary astronomical surveys (for example, the Sloan Digital Sky Survey) and are easy to download and use. The accompanying Python code is publicly available, well documented, and follows uniform coding standards. Together, the data sets and code enable readers to reproduce all the figures and examples, evaluate the methods, and adapt them to their own fields of interest. Describes the most useful statistical and data-mining methods for extracting knowledge from huge and complex astronomical data sets Features real-world data sets from contemporary astronomical surveys Uses a freely available Python codebase throughout Ideal for students and working astronomers

There is a vast amount of astronomical software on the Internet, but unless you're prepared to spend months looking for it and hours downloading it, you won't be able to match this collection!

A Practical Guide to Observational Astronomy provides a practical and accessible introduction to the ideas and concepts that are essential to making and analyzing astronomical observations. A key emphasis of the book is on how modern astronomy would be impossible without the extensive use of computers, both for the control of astronomical instruments and the subsequent data analysis. Astronomers now need to use software to access and assess the data they produce, so understanding how to use computers to control equipment and analyze data is as crucial to modern astronomers as a telescope. Therefore, this book contains an array of practical problems for readers to test their knowledge, in addition to a wealth of examples and tutorials using Python on the author’s website, where readers can download and create image processing scripts. This is an excellent study guide or textbook for an observational astronomy course for advanced undergraduate and graduate astronomy and physics students familiar with writing and running simple Python scripts. Key Features Contains the latest developments and technologies from astronomical observatories and telescope facilities on the ground and in space Accompanied by a companion website with examples, tutorials, Python scripts, and resources Authored by an observational astronomer with over thirty years of observing and teaching experience About the Author M. Shane Burns earned his BA in physics at UC San Diego in 1979. He began graduate work at UC Berkeley in 1979, where he worked on an automated search for nearby supernovae. After being awarded a PhD in 1985, Professor Burns became a postdoctoral researcher at the University of Wyoming. He spent the summer of 1988 as a visiting scientist at Lawrence Berkeley National Lab, where he helped found the Supernova Cosmology Project (SCP). He continued to work as a member of the SCP group while a faculty member at Harvey Mudd College, the US Air Force Academy, and Colorado College. The 2011 Nobel Prize in Physics was awarded to the leader of the SCP for the group’s "discovery of the accelerating expansion of the Universe through observations of distant supernovae." During his career, Professor Burns has observed using essentially all of the world’s great observatories, including the Keck Observatory and the Hubble Space Telescope.

Scientific Astrophotography is intended for those amateur astronomers who are looking for new challenges, once they have mastered visual observing and the basic imaging of various astronomical objects. It will also be a useful reference for scientifically inclined observers who want to learn the fundamentals of astrophotography with a firm emphasis on the discipline of scientific imaging. This books is not about making beautiful astronomical images; it is about recording astronomical images that are scientifically rigorous and from which accurate data can be extracted. This book is unique in that it gives readers the skills necessary for obtaining excellent images for scientific purposes in a concise and procedurally oriented manner. This not only gets the reader used to a disciplined approach to imaging to maximize quality, but also to maximize the success (and minimize the frustration!) inherent in the pursuit of astrophotography. The knowledge and skills imparted to the reader of this handbook also provide an excellent basis for “beautiful picture” astrophotography! There is a wealth of information in this book – a distillation of ideas and data presented by a diverse set of sources and based on the most recent techniques, equipment, and data available to the amateur astronomer. There are also numerous practical exercises. Scientific Astrophotography is perfect for any amateur astronomer who wants to go beyond just astrophotography and actually contribute to the science of astronomy.

A beginning to intermediate guide to obtaining and analyzing the lightcurves of asteroids and variable stars.