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Session Overview

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.

Session Activities

Lecture Video and Summary

• Watch the video lecture Lecture 16: Projection Matrices and Least Squares
• Read the accompanying lecture summary (PDF)
• Lecture video transcript (PDF)

Suggested Reading

• Read Section 4.3 in the 4^th or 5^th edition.

Problem Solving Video

• Watch the recitation video on Problem Solving: Least Squares Approximation
• Recitation video transcript (PDF)

Check Yourself

Problems and Solutions

Work the problems on your own and check your answers when you’re done.

• Problems (PDF)
• Solutions (PDF)

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