Fitting Equations to Data: Computer Analysis of Multifactor Data / Edition 2

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Overview

Helps any serious data analyst with a computer to recognize the strengths and limitations of data, to test the assumptions implicit in the least squares methods used to fit the data, to select appropriate forms of the variables, to judge which combinations of variables are most influential, and to state the conditions under which the fitted equations are applicable. This edition includes numerous extensions and new devices such as component and component-plus-residual plots, cross verification with a second sample, and an index of required x-precision; also, the search for better subset equations is enlarged to cover 262,144 alternatives. The methods described have been applied in agricultural, environmental, management, marketing, medical, physical, and social sciences. Mathematics is kept to the level of college algebra.
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Editorial Reviews

From the Publisher
"...a grand historical document for industrial statistics in its glory days, as its selection for the Classics Library implies." —Technometrics Vol. 42, No. 4 May 2001

This book provides an excellent insight into the minds of two master craftsmen at work. I very much applaud the decision to include this in a "classics library" and would encourage more authors to produce statistics books in the same vein, i.e. focused on the practical application of the subject rather than methodology development. Anyone involved in the analysis of unbalanced multifactor dtaa will find this book an extremely useful source of practical advice. —The Statistician 50 (1) 2001.

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Product Details

  • ISBN-13: 9780471053705
  • Publisher: Wiley, John & Sons, Incorporated
  • Publication date: 4/25/1980
  • Series: Wiley Series in Probability and Statistics Series , #126
  • Edition description: 2d ed
  • Edition number: 2
  • Pages: 480
  • Product dimensions: 6.30 (w) x 9.29 (h) x 1.10 (d)

Meet the Author

About the authors CUTHBERT DANIEL is a Consulting Engineering Statistician. He has specialized in applications of statistics to industrial experimentation since 1947. He has worked extensively in design of experiments and regression analysis. His numerous papers have appeared in Technometrics, the Journal of the American Statistical Association, Chemical Engineering Progress, and other journals. He read the R.A. Fisher Memorial Lecture in 1971 and the W.J. Youden Memorial Address in 1974. He was awarded the S.S. Wilks Memorial Medal in 1974. FRED S. WOOD is Senior Operations Research Analyst with the Standard Oil Company with clients in research and development, marketing, manufacturing, production, transportation, finance, and management. His articles have appeared in Technometrics, the Journal of the Society of Automotive Engineers, S.A.E. Transactions, the Oil and Gas Journal, and the Industrial and Chemical Engineering Journal. He holds a number of patents in the fields of both process and product development.
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Table of Contents

Assumptions and Methods of Fitting Equations.
One Independent Variable.
Two or More Independent Variables.
Fitting an Equation in Three Independent Variables.
Selection of Independent Variables.
Some Consequences of the Disposition of the Data Points.
Selection of Variables in Nested Data.
Nonlinear Least Squares, a Complex Example.
Glossary.
User's Manual.
Bibliography.
Index.
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