Regression Analysis Theory Methods by Sen Ashish (27 results)

Language: English
Published by Springer New York, 1990
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 1990
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Language: English
Published by Secaucus, New Jersey, U.S.A.: Springer Verlag, 1990
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Language: English
Published by Springer 1994-01, 1994
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Language: English
Published by Springer, 1994
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Language: English
Published by Springer New York, 2011
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Language: English
Published by Springer, 1994
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer New York 1990-01-01, 1990
- Softcover
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Language: English
Published by Springer New York, 1997
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em pirically identifying how a variable is affected by other variables, regression methods have become essential in a wide range of fields, including the social sciences, engineering, medical research and business. Of the various methods of performing regression, least squares is the most widely used. In fact, linear least squares regression is by far the most widely used of any statistical technique. Although nonlinear least squares is covered in an appendix, this book is mainly about linear least squares applied to fit a single equation (as opposed to a system of equations). The writing of this book started in 1982. Since then, various drafts have been used at the University of Toronto for teaching a semester-long course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, engineering, economics, forestry and the behav ioral sciences. Parts of the book have also been used in a quarter-long course given to Master's and Ph.D. students in public administration, urban plan ning and engineering at the University of Illinois at Chicago (UIC). This experience and the comments and criticisms from students helped forge the final version.…

Language: English
Published by Springer New York, 1997
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Condition: Gut. Zustand: Gut | Seiten: 368 | Sprache: Englisch | Produktart: Bücher | Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em pirically identifying how a variable is affected by other variables, regression methods have become essential in a wide range of fields, including the social sciences, engineering, medical research and business. Of the various methods of performing regression, least squares is the most widely used. In fact, linear least squares regression is by far the most widely used of any statistical technique. Although nonlinear least squares is covered in an appendix, this book is mainly about linear least squares applied to fit a single equation (as opposed to a system of equations). The writing of this book started in 1982. Since then, various drafts have been used at the University of Toronto for teaching a semester-long course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, engineering, economics, forestry and the behav ioral sciences. Parts of the book have also been used in a quarter-long course given to Master's and Ph.D. students in public administration, urban plan ning and engineering at the University of Illinois at Chicago (UIC). This experience and the comments and criticisms from students helped forge the final version.…

Language: English
Published by Springer, 2011
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Language: English
Published by New York Springer Verlag, 1990
- Hardcover
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Gebunden. Condition: Gut. " Gebraucht - Gut Zustand: Gut, Mängelexemplar, XV, 347 pp. 38 figs., 3 1/2\" diskette About this book: An up-to-date, rigorous, and lucid treatment of the theory, methods, and applications of regression analysis, and thus ideally suited for those interested in the theory as well as those whose interests lie primarily with applications. It is further enhanced through real-life examples drawn from many disciplines, showing the difficulties typically encountered in the practice of regression analysis. Consequently, this book provides a sound foundation in the theory of this important subject. Written for grade students ".…

Language: English
Published by Springer, 1990
- Hardcover
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Language: English
Published by Springer, 1994
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer New York, 2012
- Softcover
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 2011
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Language: English
Published by Springer, 1990
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Language: English
Published by Springer, 1997
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Published by Springer-Verlag, New York, 1990
- Hardcover
- First Edition
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Add to basketHardcover. Condition: Very Good. 1st Edition. 347 pages in very good condition. Pages are clean and unmarked. Previous owner's bookplate on the ffep. Page edges are lightly spotted. A sealed pouch with floppy disk at the back of the book. Bound in yellow hardcovers iwth black titles. Faded on the edges and spine. Lightly smudged. 1ST US EDITION. VG. Book.…

Language: English
Published by J.B. Metzler, 1994
- Softcover
- Print on Demand
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Any method of fitting equations to data may be called regression. Such equations are valuable for at least two purposes: making predictions and judging the strength of relationships. Because they provide a way of em pirically identifying how a variable is affected by other variables, regression methods have become essential in a wide range of fields, including the soeial seiences, engineering, medical research and business. Of the various methods of performing regression, least squares is the most widely used. In fact, linear least squares regression is by far the most widely used of any statistical technique. Although nonlinear least squares is covered in an appendix, this book is mainly ab out linear least squares applied to fit a single equation (as opposed to a system of equations). The writing of this book started in 1982. Since then, various drafts have been used at the University of Toronto for teaching a semester-Iong course to juniors, seniors and graduate students in a number of fields, including statistics, pharmacology, pharmacology, engineering, economics, forestry and the behav ioral seiences. Parts of the book have also been used in a quarter-Iong course given to Master's and Ph.D. students in public administration, urban plan ning and engineering at the University of Illinois at Chicago (UIC). This experience and the comments and critieisms from students helped forge the final version.…