Linear regression is commonly used to fit a line to a collection of data. The method of least squares can be viewed as finding the projection of a vector. Linear algebra provides a powerful and efficient description of linear regression in terms of the matrix ATA.
Lecture Video and Summary
- Watch the video lecture Projection Matrices and Least Squares (00:48:05)
Lecture 16: Projection Matrices and Least Squares
- Read the accompanying lecture summary (PDF)
- Lecture video transcript (PDF)
- Read Section 4.3 in the 4th or 5th edition.
Problem Solving Video
- Watch the recitation video on Least Squares Approximation (00:08:03)
Problem Solving: Least Squares Approximation
- Recitation video transcript (PDF)
Problems and Solutions
Work the problems on your own and check your answers when you're done.