The eighth edition of Design and Analysis of Experiments continues to provideextensive and in-depth information on engineering, business, and statistics-as well as informative ways to help readers design and analyze experiments for improving the quality, efficiency and performance of working systems. Furthermore, the text maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics innested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book. INDICE: Preface 1 Introduction to Designed Experiments1.1 Strategy of Experimentation1.2 Some Typical Applications of Experimental Design1.3 Basic Principles 1.4 Guidelines for Designing Experiments1.5 A Brief History of Statistical Design1.6 Summary: Using Statistical Techniques in Experimentation 1.7 Problems2 Basic Statistical Methods2.1 Introduction2.2 Basic Statistical Concepts2.3 Sampling and Sampling Distributions2.4 Inferences About the Differences in Means, Randomized Designs2.5 Inferences About the Differences in Means, PairedComparison Designs2.6 Inferences About the Variances of Normal Distributions2.7 Problems3 Analysis of Variance3.1 An Example3.2 The Analysis of Variance3.3Analysis of the Fixed Effects Model3.4 Model Adequacy Checking3.5 Practical Interpretation of Results3.6 Sample Computer Output3.7 Determining Sample Size3.8 Other Examples of Single-Factor Experiments3.9 The Random Effects Model3.10The Regression Approach to the Analysis of Variance3.11 Nonparametric Methodsin the Analysis of Variance3.12 Problems4 Experiments with Blocking Factors 4.1 The Randomized Complete Block Design4.2 The Latin Square Design4.3 The Graeco-Latin Square Design4.4 Balanced Incomplete Block Designs4.5 Problems5 Factorial Experiments5.1 Basic Definitions and Principles5.2 The Advantage of Factorials5.3 The Two-Factor Factorial Design5.4 The General Factorial Design5.5 Fitting Response Curves and Surfaces5.6 Blocking in a Factorial Design5.7 Problems6 Two-Level Factorial Designs6.1 Introduction6.2 The 22 Design6.3 The 23 Design6.4 The General 2k Design6.5 A Single Replicate of the 2k Design6.6 Additional Examples of Unreplicated 2k Design6.7 2k Designs are Optimal Designs6.8 The Addition of Center Points to the 2k Design6.9 Why We Work with Coded Design Variables6.10 Problems7 Blocking and Confounding Systems for Two-Level Factorials7.1 Introduction7.2 Blocking a Replicated 2k Factorial Design7.3 Confounding in the 2k Factorial Design7.4 Confounding the 2k Factorial Design in Two Blocks7.5 Another Illustration of Why Blocking Is Important7.6 Confounding the 2kFactorial Design in Four Blocks7.7 Confounding the 2k Factorial Design in 2p Blocks7.8 Partial Confounding7.9 Problems8 Two-Level Fractional Factorial Designs 8.1 Introduction8.2 The One-Half Fraction of the 2k Design8.3 The One-Quarter Fraction of the 2k Design8.4 The General 2k-p Fractional Factorial Design8.5 Alias Structures in Fractional Factorials and other Designs8.6 Resolution III Designs8.7 Resolution IV and V Designs8.8 Supersaturated Designs8.9 Summary8.10 Problems9 Other Topics on Factorial and Fractional Factorial Designs9.1 The 3k Factorial Design9.2 Confounding in the 3k Factorial Design9.3 FractionalReplication of the 3k Factorial Design9.4 Factorials with Mixed Levels9.5 Nonregular Fractional Factorial Designs9.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool9.7 Problems10 Regression Modeling10.1 Introduction10.2 Linear Regression Models10.3 Estimation of the Parameters in Linear Regression Models10.4 Hypothesis Testing in Multiple Regression10.5 Confidence Intervals in Multiple Regression10.6 Prediction of New ResponseObservations10.7 Regression Model Diagnostics10.8 Testing for Lack of Fit10.9Problems11 Response Surface Methodology11.1 Introduction to Response Surface Methodology11.2 The Method of Steepest Ascent11.3 Analysis of a Second-Order Response Surface11.4 Experimental Designs for Fitting Response Surfaces11.5 Experiments with Computer Models11.6 Mixture Experiments11.7 Evolutionary Operation11.8 Problems12 Robust Design12.1 Introduction12.2 Crossed Array Designs12.3Analysis of the Crossed Array Design12.4 Combined Array Designs and the Response Model Approach12.5 Choice of Designs12.6 Problems13 Random Effects Models13.1 Random Effects Models13.2 The Two-Factor Factorial with Random Factors13.3The Two-Factor Mixed Model13.4 Sample Size Determination with Random Effects13.5 Rules for Expected Mean Squares13.6 Approximate F Tests13.7 Some Additional Topics on Estimation of Variance Components13.8 Problems14 Experiments with Nested Factors and Hard-to-Change Factors14.1 The Two-Stage Nested Design14.2 The General m-Stage Nested Design14.3 Designs with Both Nested and Factorial Factors14.4 The Split-Plot Design14.5 Other Variations of the Split-Plot Design14.6 Problems15 Other Topics15.1 Nonnormal Responses and Transformations15.2 Unbalanced Data in a Factorial Design15.3 The Analysis of Covariance15.4 Repeated Measures15.5 ProblemsAppendixTable I. Cumulative Standard Normal DistributionTable II. Percentage Points of the t DistributionTable III. Percentage Points of the X2 DistributionTable IV. Percentage Points of the F DistributionTableV. Operating Characteristic Curves for the Fixed Effects Model Analysis of VarianceTable VI. Operating Characteristic Curves for the Random Effects Model Analysis of VarianceTable VII. Percentage Points of the Studentized Range StatisticTable VIII. Critical Values for Dunnett's Test for Comparing Treatments with a ControlTable IX. Coefficients of Orthogonal PolynomialsTable X. Alias Relationships for 2k-p Fractional Factorial Designs with k ≤ 15 and n ≤ 64BibliographyIndex
- ISBN: 978-1-118-09793-9
- Editorial: John Wiley & Sons
- Encuadernacion: Rústica
- Páginas: 680
- Fecha Publicación: 15/06/2012
- Nº Volúmenes: 1
- Idioma: Inglés