Applications of Statistics to Industrial Experimentation by Cuthbert Daniel

Applications of Statistics to Industrial Experimentation by Cuthbert Daniel

Mr. Daniel's book concerns itself with statistical aids available for the planning of industrial experiments and with the analysis and interpretation of the data collected from such experiments. In it, he questions some standard designs and procedures in analysis, contending that many can be checked only after the data are in. There are many detailed examples. Chapters 1-3: Design of multifactor industrial experiments has become routinized. In addition, analysis of resulting data is often handled by computer programs long-since outdated--programs still being taught on the university level and still part of most statistical texts. Chapter 4: Here the study of data from simple two-factor three-level designs is carried further than in other available works. Spotting and interpretation of irregular results are feasible even in such small data sets. Chapters 5-8: Size of industrial experiments is rarely determined by standard statistical criteria of power or by shortness of confidence intervals. The real criteria are usually time- and budget-restrictions, and nearness to final decision on marketability. Chapter 10: Blocking of factorial and fractional factorial plans is considered. Chapters 11-13: The rationale of fractionation of factorial designs is given in new detail. Chapter 14: Clearing up residual ambiguities after completion of a fractional design is often proposed by way of doubling the amount of work really needed. Daniel points out that much smaller augmentations are often feasible, and their selection is detailed for many cases. Chapter 15: When smooth time trends (linear and quadratic) are known to occur, more efficient and compact plans than the usual blocked designs are possible. Here they are offered. Chapter 16: Serious examples of nested designs require special care--especially in analysis. Here is a volume that should be valuable to experimenters who have some knowledge of elementary statistics (at least one year of undergraduate-level statistics), and to the statistician who seeks simple explanations, detailed examples, and documentation of the many outcomes that can be expected to occur.

About the Author Cuthbert Daniel, Consultant in Engineering Statistics, earned his B.S. and M.S. degrees in Chemical Engineering at the Massachusetts Institute of Technology, studying further at the University of Berlin in 1928 and at Harvard University, 1930-31. He has taught courses in design of experiments and industrial statistics at Columbia University and at the University of California, Berkeley. In the mid-40's he worked as a Statistician at the Gaseous Diffusion Plant, Manhattan Project, Oak Ridge, Tennessee. Mr. Daniel has served as a consultant in statistics to the Research and Development Departments of several large corporations, including Procter and Gamble, United States Steel, General Foods, Interchemical, Standard Oil (Indiana), and Okonite. Mr. Daniel has been a consultant on design of experiments and analysis of engineering data to the Office of Air Polution, and to the Consumers Union. He was a member of Cancer Clinical Investigations Review Committee of NCI, and of NAS/NRC Committee on National Statistics. He is author (with F. S. Wood) of Fitting Equations to Data: Computer Analysis of Multifactor Data for Scientists And Engineers, published by Wiley-Interscience in 1971.

SKU	Unavailable
ISBN 13	9780471194699
ISBN 10	0471194697
Title	Applications of Statistics to Industrial Experimentation
Author	Cuthbert Daniel
Series	Wiley Series In Probability And Statistics
Condition	Unavailable
Binding Type	Hardback
Publisher	Wiley-Interscience
Year published	1976-01-01
Number of pages	320
Cover note	Book picture is for illustrative purposes only, actual binding, cover or edition may vary.