Neuware -Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool.Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course.Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 682 pp. Englisch.

Bestandsnummer des Verk�ufers 9780387984544

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Bibliografische Details

Titel: Applied Regression Analysis
Verlag: Springer US, Springer New York Apr 1998
Erscheinungsjahr: 1998
Sprache: Englisch
ISBN-10: 0387984542
ISBN-13: 9780387984544
Einband: Buch
Auflage: 2. Auflage
Zustand: Neu
Abmessungen: Breite: 260 mm, H�he: 183 mm, Tiefe: 41 mm
Gewicht: 1459 Gramm

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Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool.
Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course.
Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.

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Aimed at the scientist who wishes to gain a working knowledge of regression analysis, the basic purpose of this volume is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is neither a cookbook nor a theoretical book. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching applied regression courses to graduate students in the sciences. Applied Regression Analysis serves as an excellent text for a service course on regression for nonstatisticians and also as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a theoretical linear models course.

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