Data Analysis Using the Method of Least Squares

Extracting the Most Information from Experiments

  • John Wolberg

Table of contents

  1. Front Matter
    Pages I-XIII
  2. Pages 1-29
  3. Pages 73-113
  4. Pages 115-136
  5. Pages 169-202
  6. Pages 203-238
  7. Back Matter
    Pages 239-250

About this book

Introduction

The preferred method of data analysis of quantitative experiments is the method of least squares. Often, however, the full power of the method is overlooked and very few books deal with this subject at the level that it deserves. The purpose of Data Analysis Using the Methods of Least Squares is to fill this gap and include the type of information required to help scientists and engineers apply the method to problems in their special fields of interest. In addition, graduate students in science and engineering doing work of experimental nature can benefit from this book. Particularly, both linear and non-linear least squares, the use of experimental error estimates for data weighting, procedures to include prior estimates, methodology for selecting and testing models, prediction analysis, and some non-parametric methods are discussed.

Keywords

Curve Fitting Experiment Least Squares Nonlinear Models Parametric Models Regression calculus data analysis kernel linear optimization model

Authors and affiliations

  • John Wolberg
    • 1
  1. 1.Technion-Israel Institute of TechnologyFaculty of Mechanical EngineeringHaifaIsrael

Bibliographic information

  • DOI https://doi.org/10.1007/3-540-31720-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-25674-8
  • Online ISBN 978-3-540-31720-3
  • About this book