BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Statistical Analysis of Designed Experiments : Theory and Applications

Statistical Analysis of Designed Experiments : Theory and Applications

Statistical Analysis of Designed Experiments : Theory and Applications Hardback - 2009 - 1st Edition

by Ajit C. Tamhane

Add to wish list
  • Used
  • Good
  • Hardback
Used - Good

Description

Wiley & Sons, Incorporated, John, 2009. Hardcover. Good. Disclaimer:A copy that has been read, but remains in clean condition. All pages are intact, and the cover is intact. The spine may show signs of wear. Pages can include limited notes and highlighting, and the copy can include previous owner inscriptions. At ThriftBooks, our motto is: Read More, Spend Less.Dust jacket quality is not guaranteed.
Ask the seller a question Add to wish list
A$12.06
Free Delivery within USA
Standard delivery: 4 to 8 days
More delivery options
Ships from ThriftBooks (Washington, United States)

Details

  • Title Statistical Analysis of Designed Experiments : Theory and Applications
  • Author Ajit C. Tamhane
  • Binding Hardback
  • Edition number 1st
  • Edition 1
  • Condition Used - Good
  • Pages 720
  • Volumes 1
  • Language ENG
  • Publisher Wiley & Sons, Incorporated, John, Hoboken, N.J
  • Publication date 2009
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Table of Contents
  • Bookseller's Inventory # G0471750433I3N00
  • ISBN 9780471750437 / 0471750433
  • Weight 2.4 lbs (1.09 kg)
  • Dimensions 9.3 x 6.1 x 1.6 in (23.62 x 15.49 x 4.06 cm)
  • Category Mathematics
  • Library of Congress subjects Experimental design, Lehrbuch
  • Library of Congress Catalogue Number 2008009432
  • Dewey Decimal Code 519.57
  • Quantity available 1

About ThriftBooks Washington, United States

Biblio member since 2018

From the largest selection of used titles, we put quality, affordable books into the hands of readers

Terms of Sale: 30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from ThriftBooks

Reader reviews for Statistical Analysis of Designed Experiments : Theory and Applications

From the publisher

A indispensable guide to understanding and designing modern experiments

The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences.

The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests.

Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab(R) software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets.

With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

From the rear cover

A indispensable guide to understanding and designing modern experiments

The tools and techniques of Design of Experiments (DOE) allow researchers to successfully collect, analyze, and interpret data across a wide array of disciplines. Statistical Analysis of Designed Experiments provides a modern and balanced treatment of DOE methodology with thorough coverage of the underlying theory and standard designs of experiments, guiding the reader through applications to research in various fields such as engineering, medicine, business, and the social sciences.

The book supplies a foundation for the subject, beginning with basic concepts of DOE and a review of elementary normal theory statistical methods. Subsequent chapters present a uniform, model-based approach to DOE. Each design is presented in a comprehensive format and is accompanied by a motivating example, discussion of the applicability of the design, and a model for its analysis using statistical methods such as graphical plots, analysis of variance (ANOVA), confidence intervals, and hypothesis tests.

Numerous theoretical and applied exercises are provided in each chapter, and answers to selected exercises are included at the end of the book. An appendix features three case studies that illustrate the challenges often encountered in real-world experiments, such as randomization, unbalanced data, and outliers. Minitab(R) software is used to perform analyses throughout the book, and an accompanying FTP site houses additional exercises and data sets.

With its breadth of real-world examples and accessible treatment of both theory and applications, Statistical Analysis of Designed Experiments is a valuable book for experimental design courses at the upper-undergraduate and graduate levels. It is also an indispensable reference for practicing statisticians, engineers, and scientists who would like to further their knowledge of DOE.

About the author

Ajit C. Tamhane, PhD, is Professor of Industrial Engineering and Management Sciences at Northwestern University. A Fellow of the American Statistical Society, Institute of Mathematical Statistics, American Association for Advancement of Science and an elected member of the International Statistical Institute, Dr. Tamhane has over forty years of academic and consulting experience in the areas of applied and mathematical statistics. He is the coauthor of Multiple Comparison Procedures and a forthcoming book on Predictive Analytics: Parametric Models for Regression and Classification Using R, also published by Wiley. He is also the coauthor of Statistics and Data Analysis: From Elementary to Intermediate.

tracking-