SOP For Performig BLR in Python

This document serves as a standard operating procedure (SOP) for performing Bayesian linear regression (BLR). The goals of this document are as follows: users will be familiar with the mathematics and theory behind BLR, users will be able to implement a simple example of BLR in python, and users will be able to take this knowledge and extended it to their own personal modeling situa- tions. In order to use this document successfully users will need to be familiar with gradients and their minimization properties from calculus III. Along with this, a basic understanding of statistics is required. Users are expected to under- stand the properties of normal distributions and be able to find their mean and variance. Lastly a basic understanding of Python and specifically the packages Numpy and Matplotlib

To view this project please click on the PDF link above.