Abstract
This chapter reviews the examples of least squares fit and the related max-min conditions. The basic idea of least squares fit is related to (x1, y1), (x2, y2), …, (xn, yn). These represent the output of a linear function z = mx + b, with errors introduced by measurement.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Calculus Using Mathematica: Scientific Projects and Mathematical Background
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
