Lecture Notes in Numerical Analysis with Mathematica

Lecture Notes in Numerical Analysis with Mathematica

Indexed in: EBSCO.

“ Lecture Notes in Numerical Analysis with Mathematica” highlights most of the important algorithms and their solved examples by Mathematica. The contents of this book include chapters on ...
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Introduction to the Least Squares Analysis

Pp. 133-156 (24)

Krystyna STYš and Tadeusz STYš

Abstract

This chapter is designed for the least squares method . It begins with the least squares method to determine a polynomial of degree n well fitted to m discrete points (xi, yi), i = 1, 2, ...,m, when n ≤ m. In the simplest form, the line of regression through m points is determined. The algorithm to find well fitted function to given discrete data is also presented. The Mathematica modules are designed and example illustrating the method are provided . The chapter ends with a set of questions.

Keywords:

The least squares method, Regressions.

Affiliation:

University of Warsaw, Poland.