June 2016
Beginner to intermediate
284 pages
6h 22m
English
Content preview from Mastering Python Data AnalysisBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Chapter 6. Bayesian Methods
Bayesian inference is a different paradigm for statistics; it is not a method or algorithm such as cluster finding or linear regression. It stands next to classical statistical analysis. Everything that we have done so far in this book, and everything that you can do in classical (or frequentist) statistical analysis, you can do in Bayesian statistics. The main difference between frequentist (classical) and Bayesian statistics is that while frequentist assumes that the model parameters are fixed, Bayesian assumes that they have a range, a distribution. Thus, from the frequentist approach, it is easy to create point estimates—mean, variance, or fixed model parameters—directly from the data. The point estimates are unique ...
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