An Introduction to Computational Statistics: Regression Analysis

Jennrich, R. I.:

ISBN 10: 0134548108 / ISBN 13: 9780134548104

Published by Prentice Hall, 1995

About this Item

364 pp. Cover slightly soiled and bumped, inside in good condition 371 Sprache: Englisch Gewicht in Gramm: 693.

Seller Inventory # 39910

Bibliographic Details

• Title: An Introduction to Computational Statistics: Regression Analysis
• Publisher: Prentice Hall
• Publication Date: 1995
• Language: English
• ISBN 10: 0134548108
• ISBN 13: 9780134548104
• Binding: Paperback
• Condition: Akzeptabel
• Seller catalogs:
  • Mathematik

About this title

Synopsis

This fully integrated development of the theory, computation, and practice of modern regression analysisâ both linear and nonlinear models and analysis of varianceâ features many examples and problems that involve complete analysis, from data entry to report writing. This book offers a modern, software-oriented approach. It introduces statistical software early and uses it throughout. It ignores traditional topics that have been made obsolete by easy access to statistical software. Data analysis theory and traditional theory are covered. Computational detail is explicit and the book illustrates complete data analyses for a broad variety of applications. Extensive coverage of nonlinear regression is provided, with applications to maximum likelihood estimation and robust regression.

From the Back Cover

Key Benefit: This fully integrated development of the theory, computation, and practice of modern regression analysis—both linear and nonlinear models and analysis of variance—features many examples and problems that involve complete analysis, from data entry to report writing. Key Topics: This book offers a modern, software-oriented approach. It introduces statistical software early and uses it throughout. It ignores traditional topics that have been made obsolete by easy access to statistical software. Data analysis theory and traditional theory are covered. Computational detail is explicit and the book illustrates complete data analyses for a broad variety of applications. Extensive coverage of nonlinear regression is provided, with applications to maximum likelihood estimation and robust regression.