Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
ROBERT L. MASON, PhD, is Institute Analyst at Southwest Research Institute in San Antonio, Texas.
RICHARD F. GUNST, PhD, is a professor in the Department of Statistical Science at Southern Methodist University in Dallas, Texas.
JAMES L. HESS, PhD, is Staff Vice President, Operations, at Leggett & Platt Inc. in Carthage, Missouri.
Praise for the First Edition
Statistical Design and Analysis of Experiments
"A very useful book for self study and reference."
–Journal of Quality Technology
"Very well written. It is concise and really packs a lot of material in a valuable reference book."
–Technometrics
"An informative and well-written book . . . presented in an easy-to-understand style with many illustrative numerical examples taken from engineering and scientific studies."
–Choice (American Library Association)
Practicing engineers and scientists often have a need to utilize statistical approaches to solving problems in an experimental setting. Yet many have little formal training in statistics. Statistical Design and Analysis of Experiments gives such readers a carefully selected, practical background in the statistical techniques that are most useful to experimenters and data analysts who collect, analyze, and interpret data.
The First Edition of this now-classic book garnered praise in the field. Now its authors update and revise their text, incorporating readers’ suggestions as well as a number of new developments. Statistical Design and Analysis of Experiments, Second Edition emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results, presenting statistics as an integral component of experimentation from the planning stage to the presentation of conclusions.
Giving an overview of the conceptual foundations of modern statistical practice, the revised text features discussions of:
Ideal for both students and professionals, this focused and cogent reference has proven to be an excellent classroom textbook with numerous examples. It deserves a place among the tools of every engineer and scientist working in an experimental setting.
Praise for the First Edition
Statistical Design and Analysis of Experiments
A very useful book for self study and reference.
-Journal of Quality Technology
Very well written. It is concise and really packs a lot of material in a valuable reference book.
-Technometrics
An informative and well-written book . . . presented in an easy-to-understand style with many illustrative numerical examples taken from engineering and scientific studies.
-Choice (American Library Association)
Practicing engineers and scientists often have a need to utilize statistical approaches to solving problems in an experimental setting. Yet many have little formal training in statistics. Statistical Design and Analysis of Experiments gives such readers a carefully selected, practical background in the statistical techniques that are most useful to experimenters and data analysts who collect, analyze, and interpret data.
The First Edition of this now-classic book garnered praise in the field. Now its authors update and revise their text, incorporating readers' suggestions as well as a number of new developments. Statistical Design and Analysis of Experiments, Second Edition emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results, presenting statistics as an integral component of experimentation from the planning stage to the presentation of conclusions.
Giving an overview of the conceptual foundations of modern statistical practice, the revised text features discussions of:
Ideal for both students and professionals, this focused and cogent reference has proven to be an excellent classroom textbook with numerous examples. It deserves a place among the tools of every engineer and scientist working in an experimental setting.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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