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Data Analysis Using the Method of Least Squares

Extracting the Most Information from Experiments

  • Book
  • © 2006

Overview

Authors:
  1. John Wolberg

    1. Technion-Israel Institute of Technology, Faculty of Mechanical Engineering, Haifa, Israel

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  • Develops the full power of the least-squares method

  • Enables engineers and scientists to apply the method to their specific problem

  • Deals with linear as well as with non-linear least-squares, parametric as well as non-parametric methods

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Table of contents (7 chapters)

  1. Front Matter

    Pages I-XIII
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  2. Introduction

    Pages 1-29

  3. The Method of Least Squares

    Pages 31-71

  4. Model Evaluation

    Pages 73-113

  5. Candidate Predictors

    Pages 115-136

  6. Designing Quantitative Experiments

    Pages 137-168

  7. Software

    Pages 169-202

  8. Kernel Regression

    Pages 203-238

  9. Back Matter

    Pages 239-250
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Keywords

About this book

Measurements through quantitative experiments are one of the most f- damental tasks in all areas of science and technology. Astronomers a- lyze data from asteroid sightings to predict orbits. Computer scientists - velop models for recognizing spam mail. Physicists measure properties of materials at low temperatures to understand superconductivity. Materials engineers study the reaction of materials to varying load levels to develop methods for prediction of failure. Chemical engineers consider reactions as functions of temperature and pressure. The list is endless. From the very small-scale work on DNA to the huge-scale study of black holes, quantitative experiments are performed and the data must be analyzed. Probably the most popular method of analysis of the data associated with quantitative experiments is least squares. It has been said that the method of least squares was to statistics what calculus was to mathematics. - though the method is hardly mentioned in most engineering and science undergraduate curricula, many graduate students end up using the method to analyze the data gathered as part of f their research. There is not a lot of available literature on the subject. Very few books deal with least squares at the level of detail that the subject deserves. Many books on statistics - clude a chapter on least squares but the treatment is usually limited to the simplest cases of linear least squares.

Authors and Affiliations

  • Technion-Israel Institute of Technology, Faculty of Mechanical Engineering, Haifa, Israel

    John Wolberg

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