January 2018
Beginner to intermediate
548 pages
12h 11m
English
Content preview from IPython Interactive Computing and Visualization Cookbook - Second EditionBecome 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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Getting started with Bayesian methods
In the last recipe, we used a frequentist method to test a hypothesis on incomplete data. Here, we will see an alternative approach based on Bayesian theory. The main idea is to consider that unknown parameters are random variables, just like the variables describing the experiment. Prior knowledge about the parameters is integrated into the model. This knowledge is updated as more and more data is observed.
Frequentists and Bayesians interpret probabilities differently. Frequentists interpret a probability as a limit of frequencies when the number of samples tends to infinity. Bayesians interpret it as a belief; this belief is updated as more and more data is observed.
Here, we revisit the previous coin flipping ...
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