{"product_id":"statistics-for-experimenters-9780471718130","title":"Statistics for Experimenters","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eA Classic adapted to modern times\u003c\/b\u003e  \u003cp\u003eRewritten 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.\u003c\/p\u003e \u003cp\u003eProviding 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.\u003c\/p\u003e \u003cp\u003eAmong the new topics included are:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eGraphi\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"This is a very well written book that every design engineering and design technician needs to own.\" (\u003ci\u003eIEEE Electrical Insulation Magazine\u003c\/i\u003e, May\/June 2008)  \u003cp\u003e\"…very few of our profession would fail to benefit from and enjoy reading it.\" (\u003ci\u003eJournal of the American Statistical Association\u003c\/i\u003e, December 2006)\u003c\/p\u003e \u003cp\u003e\"...belongs on the shelf on every industrial statistician. There is much wisdom and depth here, and the improvements embodied in this new edition are substantial enough to recommend it even to those who already possess the first edition.\" (\u003ci\u003eThe American Statistician\u003c\/i\u003e, November 2006)\u003c\/p\u003e \u003cp\u003e\"...remains one of the essential books in experimental design and analysis...buying the second edition is absolutely worth the effort...\" (\u003ci\u003eMAA Reviews\u003c\/i\u003e, August 18, 2006)\u003c\/p\u003e \u003cp\u003e\"…the new edition is a significant improvement on what was already a classic.\" (\u003ci\u003eAIChE Journal\u003c\/i\u003e, July 2006)\u003c\/p\u003e \u003cp\u003e\"Is it really possible to update a well-known, classic textbook and improve it? Yes, it is not only possible but it has been done.\" (\u003ci\u003eTechnometrics\u003c\/i\u003e, May 2006)\u003c\/p\u003e \u003cp\u003e\"...it often happens that there is no statistician around when you desperately need one - then it may be useful to pull this from your laboratory textbook shelf.\" (\u003ci\u003eCanadian Journal of Medical Laboratory Science\u003c\/i\u003e, February 2006)\u003c\/p\u003e \u003cp\u003e\"A very useful and valuable statistics book…highly recommended.\" (\u003ci\u003eCHOICE\u003c\/i\u003e, February 2006)\u003c\/p\u003e \u003cp\u003e\"This is an excellent book indeed. Like the first edition, this book will soon become a must for all experimenters and educators\/trainers. I would strongly recommend this book to everyone.\" (\u003ci\u003eJournal of Quality Technology\u003c\/i\u003e, January 2006)\u003c\/p\u003e \u003cp\u003e\"This text is, undoubtedly, an essential reference for all researchers and an invaluable course book for undergraduate and graduate students.\" (\u003ci\u003eMathematical Reviews\u003c\/i\u003e, 20006b)\u003c\/p\u003e \u003cp\u003e\"...this is a welcome second edition of a much loved book...valuable...\" (\u003ci\u003eInternational Statistical Institute\u003c\/i\u003e, January 2006)\u003c\/p\u003e\n\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePreface to the Second Edition.  \u003cp\u003e\u003cb\u003eChapter 1. Catalizing the Generation of Knowledge.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. The Learning Process.\u003c\/p\u003e \u003cp\u003e1.2. Important Considerations.\u003c\/p\u003e \u003cp\u003e1.3. The Experimenter’s Problem and Statistical Methods.\u003c\/p\u003e \u003cp\u003e1.4. A Typical Investigation.\u003c\/p\u003e \u003cp\u003e1.5. How to Use Statistical Techniques.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. Basics: Probability, Parameters and Statistics.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Experimental Error.\u003c\/p\u003e \u003cp\u003e2.2. Distributions.\u003c\/p\u003e \u003cp\u003e2.3. Statistics and Parameters.\u003c\/p\u003e \u003cp\u003e2.4. Measures of Location and Spread.\u003c\/p\u003e \u003cp\u003e2.5. The Normal Distribution.\u003c\/p\u003e \u003cp\u003e2.6. Normal Probability Plots.\u003c\/p\u003e \u003cp\u003e2.7. Randomness and Random Variables.\u003c\/p\u003e \u003cp\u003e2.8. Covariance and Correlation as Measures of Linear Dependence.\u003c\/p\u003e \u003cp\u003e2.9. Student’s \u003ci\u003et\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003e2.10. Estimates of Parameters.\u003c\/p\u003e \u003cp\u003e2.11. Random Sampling from a Normal Population.\u003c\/p\u003e \u003cp\u003e2.12. The Chi-Square and \u003ci\u003eF\u003c\/i\u003e Distributions.\u003c\/p\u003e \u003cp\u003e2.13. The Binomial Distribution.\u003c\/p\u003e \u003cp\u003e2.14. The Poisson Distribution.\u003c\/p\u003e \u003cp\u003eAppendix 2A. Mean and Variance of Linear Combinations of Observations.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. Comparing Two Entities: Relevant Reference Distributions, Tests and Confidence Intervals.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. Relevant Reference Sets and Distributions.\u003c\/p\u003e \u003cp\u003e3.2. Randomized Paired Comparison Design: Boys’ Shoes Example.\u003c\/p\u003e \u003cp\u003e3.3. Blocking and Randomization.\u003c\/p\u003e \u003cp\u003e3.4. Reprise: Comparison, Replication, Randomization, and Blocking in Simple Experiments.\u003c\/p\u003e \u003cp\u003e3.5. More on Significance Tests.\u003c\/p\u003e \u003cp\u003e3.6. Inferences About Data that are Discrete: Binomial Distribution.\u003c\/p\u003e \u003cp\u003e3.7. Inferences about Frequencies (Counts Per Unit): The Poisson Distribution.\u003c\/p\u003e \u003cp\u003e3.8. Contingency Tables and Tests of Association.\u003c\/p\u003e \u003cp\u003eAppendix 3A. Comparison of the Robustness of Tests to Compare Two Entities.\u003c\/p\u003e \u003cp\u003eAppendix 3B. Calculation of reference distribution from past data.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4. Comparing a Number of Entities: Randomized Blocks and Latin Squares.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. Comparing \u003ci\u003ek\u003c\/i\u003e Treatments in a Fully Randomized Design.\u003c\/p\u003e \u003cp\u003e4.2. Randomized Block Designs.\u003c\/p\u003e \u003cp\u003e4.3. A Preliminary Note on Split-Plot Experiments and their Relationship to Randomized Blocks.\u003c\/p\u003e \u003cp\u003e4.4. More than one blocking component: Latin Squares.\u003c\/p\u003e \u003cp\u003e4.5. Balanced Incomplete Block Designs.\u003c\/p\u003e \u003cp\u003eAppendix 4A. The Rationale for the Graphical ANOVA.\u003c\/p\u003e \u003cp\u003eAppendix 4B. Some Useful Latin Square, Graeco–Latin Square, and Hyper-Graeco–Latin Square Designs.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5. Factorial Designs at Two Levels: Advantages of Experimental Design.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. Introduction.\u003c\/p\u003e \u003cp\u003e5.2. Example 1: The Effects of Three Factors (Variables) on Clarity of Film.\u003c\/p\u003e \u003cp\u003e5.3. Example 2: The Effects of Three Factors on Three Physical Properties of a Polymer Solution.\u003c\/p\u003e \u003cp\u003e5.4. A 23 Factorial Design: Pilot Plant Investigation.\u003c\/p\u003e \u003cp\u003e5.5. Calculation of Main Effects.\u003c\/p\u003e \u003cp\u003e5.6. Interaction Effects.\u003c\/p\u003e \u003cp\u003e5.7. Genuine Replicate Runs.\u003c\/p\u003e \u003cp\u003e5.8. Interpretation of Results.\u003c\/p\u003e \u003cp\u003e5.9. The Table of Contrasts.\u003c\/p\u003e \u003cp\u003e5.10. Misuse of the ANOVA for 2\u003ci\u003ek\u003c\/i\u003e Factorial Experiments.\u003c\/p\u003e \u003cp\u003e5.11. Eyeing the Data.\u003c\/p\u003e \u003cp\u003e5.12. Dealing with More Than One Response: A Pet Food Experiment.\u003c\/p\u003e \u003cp\u003e5.13. A 24 Factorial Design: Process Development Study.\u003c\/p\u003e \u003cp\u003e5.14. Analysis Using Normal and Lenth Plots.\u003c\/p\u003e \u003cp\u003e5.15. Other Models for Factorial Data.\u003c\/p\u003e \u003cp\u003e5.16. Blocking the 2\u003ci\u003ek\u003c\/i\u003e Factorial Designs.\u003c\/p\u003e \u003cp\u003e5.17. Learning by Doing.\u003c\/p\u003e \u003cp\u003e5.18. Summary.\u003c\/p\u003e \u003cp\u003eAppendix 5A. Blocking Larger Factorial Designs.\u003c\/p\u003e \u003cp\u003eAppendix 5B. Partial Confounding.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6. Fraction Factorial Designs: Economy in Experimentation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1. Effects of Five Factors on Six Properties of Films in Eight Runs.\u003c\/p\u003e \u003cp\u003e6.2. Stability of New Product, Four Factors in Eight Runs, a 24−1 Design.\u003c\/p\u003e \u003cp\u003e6.3. A Half-Fraction Example: The Modification of a Bearing.\u003c\/p\u003e \u003cp\u003e6.4. The Anatomy of the Half Fraction.\u003c\/p\u003e \u003cp\u003e6.5. The 27−4III Design: A Bicycle Example.\u003c\/p\u003e \u003cp\u003e6.6. Eight-Run Designs.\u003c\/p\u003e \u003cp\u003e6.7. Using Table 6.6: An Illustration.\u003c\/p\u003e \u003cp\u003e6.8. Sign Switching, Foldover, and Sequential Assembly.\u003c\/p\u003e \u003cp\u003e6.9. An Investigation Using Multiple-Column Foldover.\u003c\/p\u003e \u003cp\u003e6.10. Increasing Design Resolution from III to IV by Foldover.\u003c\/p\u003e \u003cp\u003e6.11. Sixteen-Run Designs.\u003c\/p\u003e \u003cp\u003e6.12. The 25−1 Nodal Half Replicate of the 25 Factorial: Reactor Example.\u003c\/p\u003e \u003cp\u003e6.13. The 28−4 IV Nodal Sixteenth Fraction of a 28 Factorial.\u003c\/p\u003e \u003cp\u003e6.14. The 215−11 III Nodal Design: The Sixty-Fourth Fraction of the 215 Factorial.\u003c\/p\u003e \u003cp\u003e6.15. Constructing Other Two-Level Fractions.\u003c\/p\u003e \u003cp\u003e6.16. Elimination of Block Effects.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7. Other Fractionals, Analysis and Choosing Follow-up Runs.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1. Plackett and Burman Designs.\u003c\/p\u003e \u003cp\u003e7.2. Choosing Follow-Up Runs.\u003c\/p\u003e \u003cp\u003e7.3. Justifications for the Use of Fractionals.\u003c\/p\u003e \u003cp\u003eAppendix 7A. Technical Details.\u003c\/p\u003e \u003cp\u003eAppendix 7B. An Approximate Partial Analysis for PB Designs.\u003c\/p\u003e \u003cp\u003eAppendix 7C. Hall’s Orthogonal Designs.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8. Factorial Designs and Data Transformation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1. A Two-Way (Factorial) Design.\u003c\/p\u003e \u003cp\u003e8.2. Simplification and Increased Sensitivity from Transformation.\u003c\/p\u003e \u003cp\u003eAppendix 8A. Rationale for Data Transformation.\u003c\/p\u003e \u003cp\u003eAppendix 8B. Bartlett’s \u003ci\u003eχ\u003c\/i\u003e2\u003ci\u003eν\u003c\/i\u003e for Testing Inhomogeneity of Variance.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9. Multiple Sources of Variation: Split Plot Designs, Variance Components and Error Transmission.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1. Split-Plot Designs, Variance Components, and Error Transmission.\u003c\/p\u003e \u003cp\u003e9.2. Split-Plot Designs.\u003c\/p\u003e \u003cp\u003e9.3. Estimating Variance Components.\u003c\/p\u003e \u003cp\u003e9.4. Transmission of Error.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10. Least Squares and Why You Need to Design Experiments.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1. Estimation With Least Squares.\u003c\/p\u003e \u003cp\u003e10.2. The Versatility of Least Squares.\u003c\/p\u003e \u003cp\u003e10.3. The Origins of Experimental Design.\u003c\/p\u003e \u003cp\u003e10.4. Nonlinear Models.\u003c\/p\u003e \u003cp\u003eAppendix 10A. Vector Representation of Statistical Concepts.\u003c\/p\u003e \u003cp\u003eAppendix 10B. Matrix Version of Least Squares.\u003c\/p\u003e \u003cp\u003eAppendix 10C. Analysis of Factorials, Botched and Otherwise.\u003c\/p\u003e \u003cp\u003eAppendix 10D. Unweighted and Weighted Least Squares.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11. Modelling Relationships, Sequential Assembly: Basics for Response Surface Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1. Some Empirical Models.\u003c\/p\u003e \u003cp\u003e11.2. Some Experimental Designs and the Design Information Function.\u003c\/p\u003e \u003cp\u003e11.3. Is the Surface Sufficiently Well Estimated?\u003c\/p\u003e \u003cp\u003e11.4. Sequential Design Strategy.\u003c\/p\u003e \u003cp\u003e11.5. Canonical Analysis.\u003c\/p\u003e \u003cp\u003e11.6. Box–Behnken Designs.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12. Some Applications of Response Surface Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1. Iterative Experimentation To Improve a Product Design.\u003c\/p\u003e \u003cp\u003e12.2. Simplification of a Response Function by Data Transformation.\u003c\/p\u003e \u003cp\u003e12.3. Detecting and Exploiting Active and Inactive Factor Spaces for Multiple-Response Data.\u003c\/p\u003e \u003cp\u003e12.4. Exploring Canonical Factor Spaces.\u003c\/p\u003e \u003cp\u003e12.5. From Empiricism to Mechanism.\u003c\/p\u003e \u003cp\u003e12.6. Uses of RSM.\u003c\/p\u003e \u003cp\u003eAppendix 12A. Average Variance of ˆ\u003ci\u003ey.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAppendix 12B.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13. Designing Robust Products: An Introduction.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1. Environmental Robustness.\u003c\/p\u003e \u003cp\u003e13.2. Robustness To Component Variation.\u003c\/p\u003e \u003cp\u003eAppendix 13A. A Mathematical Formulation for Environmental Robustness.\u003c\/p\u003e \u003cp\u003eAppendix 13B. Choice of Criteria.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14. Process Control, Forecasting and Times Series: An Introduction.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1. Process Monitoring.\u003c\/p\u003e \u003cp\u003e14.2. The Exponentially Weighted Moving Average.\u003c\/p\u003e \u003cp\u003e14.3. The CuSum Chart.\u003c\/p\u003e \u003cp\u003e14.4. Process Adjustment.\u003c\/p\u003e \u003cp\u003e14.5. A Brief Look At Some Time Series Models and Applications.\u003c\/p\u003e \u003cp\u003e14.6. Using a Model to Make a Forecast.\u003c\/p\u003e \u003cp\u003e14.7. Intervention Analysis: A Los Angeles Air Pollution Example.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15. Evolutionary Process Operation.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1. More than One Factor.\u003c\/p\u003e \u003cp\u003e15.2. Multiple Responses.\u003c\/p\u003e \u003cp\u003e15.3. The Evolutionary Process Operation Committee.\u003c\/p\u003e \u003cp\u003eReferences and Further Reading.\u003c\/p\u003e \u003cp\u003eAppendix Tables.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAuthor Index.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSubject Index.\u003c\/b\u003e\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402660290903,"sku":"9780471718130","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471718130.jpg?v=1730481148","url":"https:\/\/bookcurl.com\/products\/statistics-for-experimenters-9780471718130","provider":"Book Curl","version":"1.0","type":"link"}