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.
Rezensionen / Stimmen
"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
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Editions-Typ
Produkt-Hinweis
Illustrationen
Worked examples or Exercises; 26 Tables, black and white; 7 Halftones, unspecified; 82 Line drawings, unspecified
Maße
Höhe: 229 mm
Breite: 152 mm
Dicke: 20 mm
Gewicht
ISBN-13
978-0-521-73249-9 (9780521732499)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
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.
Autor*in
University of British Columbia, Vancouver
1. Decision; 2. Probability; 3. Statistics and expectations; 4. Correlation and association; 5. Hypothesis-testing; 6. Data modelling and parameter-estimation: basics; 7. Data modelling and parameter-estimation: advanced topics; 8. Detection and surveys; 9. Sequential data - 1D statistics; 10. Statistics of large-scale structure; 11. Epilogue: statistics and our Universe; Appendices; References; Index.
