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Recipes for a Good Statistical Analysis Read chapter Read first chapter

2015 | OriginalPaper | Chapter

5. The Prior

Authors : Stefano Andreon, Brian Weaver

Published in: Bayesian Methods for the Physical Sciences

Publisher: Springer International Publishing

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Abstract

All statistical analyses make assumptions, and Bayesian analyses are no exception. This chapter emphasizes that results depend on data and priors (assumptions). We illustrate this concept with examples where the prior plays greatly different roles, from major to negligible. We also provide some advice on how to look for information useful for sculpting the prior.

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previous chapter Single Parameter Models
next chapter Multi-parameters Models
Footnotes
1
This section can be skipped the first time through.
 
2
This section can be skipped the first time through.
 
Literature
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Metadata
Title
The Prior
Authors
Stefano Andreon
Brian Weaver
Copyright Year
2015
Book
Bayesian Methods for the Physical Sciences

Print ISBN: 978-3-319-15286-8

Electronic ISBN: 978-3-319-15287-5

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-15287-5_5

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