/BiteSizeBayes

An introduction to Bayesian statistics using Python and (coming soon) R.

Primary LanguageJupyter NotebookMIT LicenseMIT

Bite Size Bayes

Bite Size Bayes is an introduction to Bayesian statistics using Python and (coming soon) R. It does not assume any previous knowledge of probability or Bayesian methods.

This material is a work in progress, so suggestions are welcome. The best way to provide feedback is to click here and create an issue in this GitHub repository.

The notebooks

For each of the notebooks below, you have two options: if you view the notebook on NBViewer, you can read it, but you can't run the code. If you run the notebook on Colab, you'll be able to run the code, do the exercises, and save your modified version of the notebook in a Google Drive (if you have one).

Notebook 1

The Linda Problem:

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Notebook 2

Bayes's Theorem:

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Notebook 3

The Cookie Problem:

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Notebook 4

The Dice Problem:

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Notebook 5

Interpreting medical tests:

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Notebook 6

The probability mass function:

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or click here to read it on NBViewer

Notebook 7

The Euro problem:

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Notebook 8

The World Cup problem:

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Notebook 9

The World Cup problem, part two:

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Notebook 10

Joint distributions:

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Notebook 11

Comparisons:

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Notebook 12

The Binomial Distribution:

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Notebook 13

The Price Is Right Problem:

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or click here to read it on NBViewer