Rewritten and updated, this new edition of Statistics for Experimenters adopts the same approaches as the landmark First Edition by teaching with examples, readily understood graphics, and the appropriate use of computers. Catalyzing innovation, problem solving, and discovery, the Second Edition provides experimenters with the scientific and statistical tools needed to maximize the knowledge gained from research data, illustrating how these tools may best be utilized during all stages of the investigative process. The authors’ practical approach starts with a problem that needs to be solved and then examines the appropriate statistical methods of design and analysis.
Providing even greater accessibility for its users, the Second Edition is thoroughly revised and updated to reflect the changes in techniques and technologies since the publication of the classic First Edition.
Among the new topics included are:
All the computations in the Second Edition can be done utilizing the statistical language R. Functions for displaying ANOVA and lamba plots, Bayesian screening, and model building are all included and R packages are available online. All theses topics can also be applied utilizing easy-to-use commercial software packages.
Complete with applications covering the physical, engineering, biological, and social sciences, Statistics for Experimenters is designed for individuals who must use statistical approaches to conduct an experiment, but do not necessarily have formal training in statistics. Experimenters need only a basic understanding of mathematics to master all the statistical methods presented. This text is an essential reference for all researchers and is a highly recommended course book for undergraduate and graduate students.
頁數:672
版次:第2版
年份:2005年
規格:精裝/單色
ISBN:9780471718130
Chapter 1. Catalizing the Generation of Knowledge.
Chapter 2. Basics: Probability, Parameters and Statistics.
Chapter 3. Comparing Two Entities: Relevant Reference Distributions, Tests and Confidence Intervals.
Chapter 4. Comparing a Number of Entities: Randomized Blocks and Latin Squares.
Chapter 5. Factorial Designs at Two Levels.
Chapter 6. Fraction Factorial Designs.
Chapter 7. Additional Fractionals and Analysis.
Chapter 8. Factorial Designs and Data Transformation.
Chapter 9. Multiple Sources of Variation.
Chapter 10. Least Squares and Why You Need to Design Experiments.
Chapter 11. Modelling, Geometry, and Experimental Design.
Chapter 12. Some Applications of Response Surface Methods.
Chapter 13. Designing Robust Products and Processes: An Introduction.
Chapter 14. Process Control, Forecasting and Times Series: An Introduction.
Chapter 15. Evolutionary Process Operation.