Free PDF Practical Statistics for Astronomers (Cambridge Observing Handbooks for Research Astronomers), by J. V. Wall, C. R. Jenkins
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Practical Statistics for Astronomers (Cambridge Observing Handbooks for Research Astronomers), by J. V. Wall, C. R. Jenkins
Free PDF Practical Statistics for Astronomers (Cambridge Observing Handbooks for Research Astronomers), by J. V. Wall, C. R. Jenkins
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Astronomy needs statistical methods to interpret data, but statistics is a many-faceted subject that is difficult for non-specialists to access. This handbook helps astronomers analyze the complex data and models of modern astronomy. This Second Edition has been revised to feature many more examples using Monte Carlo simulations, and now also includes Bayesian inference, Bayes factors and Markov chain Monte Carlo integration. Chapters cover basic probability, correlation analysis, hypothesis testing, Bayesian modelling, time series analysis, luminosity functions and clustering. Exercises at the end of each chapter guide readers through the techniques and tests necessary for most observational investigations. The data tables, solutions to problems, and other resources are available online at www.cambridge.org/9780521732499. Bringing together the most relevant statistical and probabilistic techniques for use in observational astronomy, this handbook is a practical manual for advanced undergraduate and graduate students and professional astronomers.
- Sales Rank: #738296 in Books
- Brand: Brand: Cambridge University Press
- Published on: 2012-05-21
- Released on: 2012-04-26
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x .79" w x 5.98" l, 1.35 pounds
- Binding: Paperback
- 374 pages
- Used Book in Good Condition
Review
"Bringing together the most relevant statistical and probabilistic techniques for use in observational astronomy, this handbook is a practical manual for advanced undergraduate and graduate students and professional astronomers." -Mathematical Reviews
About the Author
J. V. Wall is Adjunct Professor in the Department of Physics and Astronomy, University of British Columbia and Visiting Professor at the University of Oxford.
C. R. Jenkins is a Research Scientist in Earth Sciences and Resource Engineering at the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia.
Most helpful customer reviews
11 of 11 people found the following review helpful.
An excellent text on astrostatistics
By Joseph Hilbe
Wall and Jenkins have produced an excellent introduction to astrostatistics, the
discipline that is foremost interested in the statistical analysis of astronomical data.
The book is clearly written for astronomers and for students in astronomy. However, it
is also of good value to statisticians who already understand the statistics, but not
necessarily the appropriate application of various statistical analyses to astronomical
and cosmological data. I found the book most useful to myself in that respect.
The text initially developed into a book from course notes used by the lead author for
teaching statistical methods to astronomy undergraduates and graduates at the University
of British Columbia beginning in 1977. The first edition of the text was published in 2003,
following some quarter of a century of maturation. Now, some nine years later, the second
edition of the book hs been published. The text has improved as a result of feedback from
students, profs who adopted the text, and others who read the book, as well as from the
authors own evaluation. New developments have also taken place in astronomy, which are
also reflected in the text.
The primary enhancement for the second edition is the focus on Bayesian methods and the
use of MCMC and Metroplis-Hastings/Gibbs sampling. Bayes inference is introduced in the
second chapter, and runs throughout the text. On the other hand, the authors have maintained,
and improved, the discussion of frequency-based statistics that is commnon to introductory
statistics courses. The text goes well beyond standard intro courses though in that survival
methods, spatial modeling, sequential analysis, signal detection, and other analytic techniques
important to astronomy are also addressed. I particularly enjoyed the final chapters which
deal with large scale structures including galaxy distribution statistics, galaxy formation,
weak lensing statistics, and nine pages devoted to the statistics of the cosmic microwave
background (CMB) universe.
Fourteen separate tables are provided in the Appendix for statistical testing. A host
of web sites for additional information are given throughout the text, which substantially
adds to the scope of the book. The data used in the text for examples are available on
the publishers web site for the book, as are the answers for the end-chapter exercise
questions. The answers given to these questions are not quick responses, but rather are
given as answers together with thoughful and thorough explanations.
I highly recommend this text for anyone with a background or interest in astronomy who
is also interested in the statistical analysis of cosmic data. I might add that the text
is very well written and engaging -- a difficult thing to do for such a subject area.
Joseph Hilbe
Chair, ISI International Astrostatistics Network
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