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Fitting Equations to Data WCL P: Computer Analysis of Multifactor Data: 75 (Wiley Classics Library) - Softcover
Synopsis
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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About the Author
Cuthbert Daniel, Consultant in Engineering Statistics, earned his B.S. and M.S. degrees in Chemical Engineering at the Massachusetts Institute of Technology, studying further at the University of Berlin in 1928 and at Harvard University, 1930-31. He has taught courses in design of experiments and industrial statistics at Columbia University and at the University of California, Berkeley. In the mid-40's he worked as a Statistician at the Gaseous Diffusion Plant, Manhattan Project, Oak Ridge, Tennessee. Mr. Daniel has served as a consultant in statistics to the Research and Development Departments of several large corporations, including Procter and Gamble, United States Steel, General Foods, Interchemical, Standard Oil, and Okonite. Mr. Daniel has been a consultant on design of experiments and analysis of engineering data to the Office of Air Polution, and to the Consumers Union. He was a member of Cancer Clinical Investigations Review Committee of NCI, and of NAS/NRC Committee on National Statistics. He is author of Fitting Equations to Data: Computer Analysis of Multifactor Data for Scientists And Engineers, published by Wiley-Interscience in 1971.
From the Back Cover
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.
From the Inside Flap
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.
"About this title" may belong to another edition of this title.
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