Statistical Challenges in Astronomy
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"Statistical Challenges in Astronomy" by Eric D. Feigelson, G. Jogesh Babu is a mathematics book and learning resource focused on Equipment & Methods. Best for teachers, students, and readers looking for stronger mathematical understanding.
Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.
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"Statistical Challenges in Astronomy" by Eric D. Feigelson, G. Jogesh Babu is a mathematics book and learning resource focused on Equipment & Methods. Best for teachers, students, and readers looking for stronger mathematical understanding.
Topic: Equipment & Methods
Author: Eric D. Feigelson, G. Jogesh Babu
Who this is for:
- Teachers and classroom instructors
- Students building subject mastery
- Readers looking for practical learning support
Why this book matters: It stands out as a practical math resource that helps explain concepts, strengthen problem-solving, and support classroom or independent learning.
Digital sky surveys, high-precision astrometry from satellite data, deep-space data from orbiting telescopes, and the like have all increased the quantity and quality of astronomical data by orders of magnitude per year for several years. Making sense of this wealth of data requires sophisticated statistical techniques. Fortunately, statistical methodologies have similarly made great strides in recent years. Powerful synergies thus emerge when astronomers and statisticians join in examining astrostatistical problems and approaches. The book begins with an historical overview and tutorial articles on basic cosmology for statisticians and the principles of Bayesian analysis for astronomers. As in earlier volumes in this series, research contributions discussing topics in one field are joined with commentary from scholars in the other. Thus, for example, an overview of Bayesian methods for Poissonian data is joined by discussions of planning astronomical observations with optimal efficiency and nested models to deal with instrumental effects. The principal theme for the volume is the statistical methods needed to model fundamental characteristics of the early universe on its largest scales.
| Author | Eric D. Feigelson, G. Jogesh Babu |
| Publisher | Springer Science & Business Media |
| Published | 2003-01-14 |
| ISBN-13 | 9780387955469 |
| Binding | Hardcover |
| Pages | 532 |
| Language | English |
| Subjects | Mathematics |
| Topic | Equipment & Methods |
Format: Hardcover
Length: 532 pages
Language: English
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