Projection Matrices and Least Squares

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Taught by OCW
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Lesson Description:

Projection Matrices and Least Squares -- Lecture 16. Review of projection matrices, orthogonality, and a discussion of least squares matrices and computation of best straight line.

Gilbert Strang, 18.06 Linear Algebra, Spring 2005. (Massachusetts Institute of Technology: MIT OpenCourseWare), http://ocw.mit.edu (Accessed November 22, 2008). License: Creative Commons BY-NC-SA.
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Additional Resources:
Questions answered by this video:
  • How do you find a least squares matrix?
  • What is a best fit line?
  • What is a best straight line?
  • How do you find the best fit line for a data set?
  • What is x hat?
  • Staff Review

    • Currently 4.0/5 Stars.
    This video talks a lot more about projections and orthogonal spaces as a lead-in to finding a least-squares matrix for a data set. By minimizing the error of a straight line through data points, it is explained how to do linear regression to find the best fit line. A great explanation of what is going on, why it works, and how to find the best straight line.