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Titlebook: Bayesian Methods for the Physical Sciences; Learning from Exampl Stefano Andreon,Brian Weaver Book 2015 Springer Nature Switzerland AG 2015

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The Prior,ptions). 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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Non-random Data Collection,vents or objects are over–represented in samples and difficult–to–collect are under–represented if not missing altogether. In this chapter we show how to account for non–random data collection to infer the properties of the population from the studied sample.
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Fitting Regression Models,ment errors of different amplitudes and an intrinsic variety in the studied populations, or an extra source of variability? A number of examples illustrate how to answer these questions and how to predict the value of an unavailable quantity by exploiting the existence of a trend with another, available, quantity.
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Book 2015 the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The ex
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