This is a very brief tutorial that describes the origins of the least squares method in statistics and how this technique is linked to linear algebra.
Many are familiar with the least squares method of finding the closest fit to a dataset, or executing linear regression. However, not many know that this method also originates in linear algebra.
This tutorial provides a very brief overview of why the method makes sense from the linear algebra perspective and what logic is followed to articulate the steps that lead towards the so-called normal equations.
The spreadsheets with all the calculations are placed here, and the paper containing the tutorial in PDF format can be downloaded or viewed from here.