Bayesian simulation of a biased coin (PDF)

This article provides an introduction to the Bayesian updating process using the example of a biased coin. It shows how the distribution narrows, and likelihood increases as more data is gathered. It is intended to sharpen your understanding of how to interpret the PDF (probability density function). A Python 3 example is given, which should help readers gain intuitions into the mechanics of the process.

About mcturra2000

Computer programmer living in Scotland.
This entry was posted in Uncategorized. Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s