This graduate textbook introduces the design of experiments with factorial structures, random factor effects, and quantitative predictors and factors, and methods for analyzing the resulting data. The second edition expands coverage of three-level fractional factorial experiments, and the analysis of data from unbalanced experiments, incomplete block designs, split-block designs, and process improvement designs. Annotation (c) Book News, Inc., Portland, OR (booknews.com)
Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results.
- Features numerous examples using actual engineering and scientific studies.
- Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions.
- Deep and concentrated experimental design coverage, with equivalent but separate emphasis on the analysis of data from the various designs.
- Topics can be implemented by practitioners and do not require a high level of training in statistics.
- New edition includes new and updated material and computer output.
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| PART I: FUNDAMENTAL STATISTICAL CONCEPTS. |
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Statistics in Engineering and Science. |
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Fundamentals of Statistical Inference. |
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Inferences on Means and Standard Deviations. |
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| PART II: DESIGN AND ANALYSIS WITH FACTORIAL STRUCTURE. |
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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.
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