Fundamental Concepts in the Design of Experiments

Turner Jr., Kenneth V.,Hicks, Charles R.

ISBN 10: 0195122739 / ISBN 13: 9780195122732

Editore: Oxford University Press, 1999

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Codice articolo S_437462510

Dati bibliografici

• Titolo: Fundamental Concepts in the Design of Experiments
• Editore: Oxford University Press
• Data di pubblicazione: 1999
• Lingua: Inglese
• ISBN 10: 0195122739
• ISBN 13: 9780195122732
• Rilegatura: Hardcover
• Edizione: quinta edizione o successive
• Condizione: Acceptable

Descrizione articolo

Riassunto

This text is a solid revision and redesign of Charles Hicks's comprehensive fourth edition of Fundamental Concepts in the Design of Experiments. It covers the essentials of experimental design used by applied researchers in solving problems in the field. It is appropriate for a variety of experimental methods courses found in engineering and statistics departments. Students learn to use applied statistics for planning, running, and analysing an experiment. The text includes 350+ problems taken from the author's actual industrial consulting experiences to give students valuable practice with real data and problem solving. About 60 new problems have been added for this edition. SAS (Statistical Analysis System) computer programs are incorporated to facilitate analysis. There is extensive coverage of the analysis of residuals, the concepts of resolution in fractional replications, the Plackett-Burman designs, and Taguchi techniques. The new edition will place a greater emphasis on computer use, include additional problems, and add computer outputs from statistical packages like Minitab, SPSS, and JMP.
The book is written for anyone engaged in experimental work who has a good background in statistical inference. It will be most profitable reading to those with a background in statistical methods including analysis of variance. This text is suitable for senior undergraduate/graduate level students in mathematics, statistics, or engineering. It is appropriate for a variety of experimental methods courses found in engineering and statistics deparmtents -- majors in this course are usually in applied statistics; non-majors, in industrial and electrical engineering, or education and life sciences.