Statistics for experimenters : design, innovation, and discovery / George E.P. Box, J. Stuart Hunter, William G. Hunter.
By: Box, George E. P
Contributor(s): Hunter, J. Stuart | Hunter, William GordonMaterial type: TextLanguage: English Series: Wiley series in probability and statisticsPublisher: Hoboken, N.J. : Wiley-Interscience, c2005Edition: 2nd edDescription: xvii, 633 p. : ill. ; 25 cmISBN: 9780471718130 (acidfree paper); 0471718130 (acidfree paper)Subject(s): Experimental design | Analysis of variance | Mathematical statisticsDDC classification: 519.5 STA LOC classification: QA279 | .B69 2005Online resources: Table of contents only | Contributor biographical information | Publisher description | OCLC | Ebook Fulltext
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Includes bibliographical references and indexes.
Catalyzing the generation of knowledge --
Basics (probability, parameters and statistics) --
Comparing two entities : relevant reference distributions, tests, and confidence intervals --
Comparing a number of entities, randomized blocks and Latin squares --
Factorial designs at two levels --
Fraction factorial designs --
Additional fractionals and analysis --
Factorial designs and data transformation --
Multiple sources of variation --
Least squares and why we need designed experiments --
Modeling, geometry, and experimental design --
Some applications of response surface methods --
Designing robust products and processes --Process control, forecasting, and times series : an introduction --
Evolutionary process operation.
The second edition of Statistics for Experimenters focuses on applications in the physical, engineering, biological, and social sciences. From the beginning, the book's source of ideas is the scientific method itself and the need of the investigator to make his or her research as effective as possible through proper choice and conduct of experiments and appropriate analysis of data. After a problem is stated, appropriate statistical methods of design and analysis are discussed. And frequently, examples are presented for which standard mathematical assumptions are wrong, thus forcing the reader's attention onto the essential precautions necessary in the conduct of the experiment to ensure valid conclusions.