erood / BiteSizeBayes

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

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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or click here to read it on NBViewer

Notebook 2

Bayes's Theorem:

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or click here to read it on NBViewer

Notebook 3

The Cookie Problem:

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or click here to read it on NBViewer

Notebook 4

The Dice Problem:

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or click here to read it on NBViewer

Notebook 5

Interpreting medical tests:

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or click here to read it on NBViewer

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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or click here to read it on NBViewer

Notebook 8

The World Cup problem:

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or click here to read it on NBViewer

Notebook 9

The World Cup problem, part two:

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or click here to read it on NBViewer

Notebook 10

Joint distributions:

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Notebook 11

Joint distributions:

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or click here to read it on NBViewer

Notebook 12

Hypothesis testing:

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or click here to read it on NBViewer