本书内容包括简单比较试验、2k因素设计、响应曲面方法和设计、稳健参数设计和过程稳健性研究、随机因素试验、巢和分图设计等。作者给出了教学建议；还有提供给老师及学生的支持材料，如补充材料，习题解答，教学PPT文件等。适合作为统计人员、自然科学研究人员、工程技术人员、管理人员和教师进行科学试验设计与分析的参考书，也可用于农业类、生物类、统计类的高年级本科生、研究生的教学参考用书。

本书是关于试验设计与分析的入门教材，是作者在亚利桑那州立大学、华盛顿大学和乔治亚工程学院三所大学近30年试验设计教学经验的基础上编写的。内容包括简单比较试验、2k因素设计、响应曲面方法和设计、稳健参数设计和过程稳健性研究、随机因素试验、巢和分图设计等。作者给出了教学建议；还有提供给老师及学生的支持材料，如补充材料，习题解答，教学PPT文件等。

本书适合作为统计人员、自然科学研究人员、工程技术人员、管理人员和教师进行科学试验设计与分析的参考书，也可用于农业类、生物类、统计类的高年级本科生、研究生的教学参考用书。

  Chapter 1　Introduction　1

  1-1　Strategy of Experimentation　1

  1-2　Some Typical Applications of Experimental Design　8

  1-3　Basic Principles　12

  1-4　Guidelines for Designing Experiments　14

  1-5　A Brief History of Statistical Design　19

  1-6　Summary: Using Statistical Techniques in Experimentation　21

  1-7　Problems　22

  Chapter 2　Simple Comparative Experiments　23

  2-1　Introduction　23

  2-2　Basic Statistical Concepts　24

  2-3　Sampling and Sampling Distributions　28

  2-4　Inferences about the Differences in Means, Randomized Designs　34

  2-4.1　Hypothesis Testing　34

  2-4.2　Choice of Sample Size　41

  2-4.3　Confidence Intervals　43

  2-4.4　The Case Where 　45

  2-4.5　The Case Where and Are Known　45

  2-4.6　Comparing a Single Mean to a Specified Value　46

  2-4.7　Summary　47

  2-5　Inferences about the Differences in Means, Paired Comparison Designs　48

  2-5.1　The Paired Comparison Problem　48

  2-5.2　Advantages of the Paired Comparison Design　51

  2-6　Inferences about the Variances of Normal Distributions　52

  2-7　Problems　54

  Chapter 3　Experiments with a Single Factor: The Analysis of Variance　60

  3-1　An Example　61

  3-2　The Analysis of Variance　63

  3-3　Analysis of the Fixed Effects Model　65

  3-3.1　Decomposition of the Total Sum of Squares　66

  3-3.2　Statistical Analysis　68

  3-3.3　Estimation of the Model Parameters　73

  3-3.4　Unbalanced Data　75

  3-4　Model Adequacy Checking　75

  3-4.1　The Normality Assumption　76

  3-4.2　Plot of Residuals in Time Sequence　78

  3-4.3　Plot of Residuals Versus Fitted Values　79

  3-4.4　Plots of Residuals Versus Other Variables　84

  3-5　Practical Interpretation of Results　85

  3-5.1　A Regression Model　85

  3-5.2　Comparisons Among Treatment Means　87

  3-5.3　Graphical Comparisons of Means　87

  3-5.4　Contrasts　88

  3-5.5　Orthogonal Contrasts　91

  3-5.6　Scheff??s Method for Comparing All Contrasts　93

  3-5.7　Comparing Pairs of Treatment Means　94

  3-5.8　Comparing Treatment Means with a Control　97

  3-6　Sample Computer Output　98

  3-7　Determining Sample Size　101

  3-7.1　Operating Characteristic Curves　101

  3-7.2　Specifying a Standard Deviation Increase　104

  3-7.3　Confidence Interval Estimation Method　104

  3-8　Discovering Dispersion Effects　105

  3-9　The Regression Approach to the Analysis of Variance　107

  3-9.1　Least Squares Estimation of the Model Parameters　107

  3-9.2　The General Regression Significance Test　108

  3-10　Nonparametric Methods in the Analysis of Variance　110

  3-10.1　The KruskalDWallis Test　110

  3-10.2　General Comments on the Rank Transformation　112

  3-11　Problems　112

  Chapter 4　Randomized Blocks, Latin Squares, and Related Designs　119

  4-1　The Randomized Complete Block Design　119

  4-1.1　Statistical Analysis of the RCBD　121

  4-1.2　Model Adequacy Checking　128

  4-1.3　Some Other Aspects of the Randomized Complete Block Design　130

  4-1.4　Estimating Model Parameters and the General Regression Significance Test　133

  4-2　The Latin Square Design　136

  4-3　The Graeco-Latin Square Design　142

  4-4　Balanced Incomplete Block Designs　145

  4-4.1　Statistical Analysis of the BIBD　146

  4-4.2　Least Squares Estimation of the Parameters　150

  4-4.3　Recovery of Interblock Information in the BIBD　152

  4-5　Problems　154

  Chapter 5　Introduction to Factorial Designs　160

  5-1　Basic Definitions and Principles　160

  5-2　The Advantage of Factorials　163

  5-3　The Two-Factor Factorial Design　164

  5-3.1　An Example　164

  5-3.2　Statistical Analysis of the Fixed Effects Model　167

  5-3.3　Model Adequacy Checking　172

  5-3.4　Estimating the Model Parameters　175

  5-3.5　Choice of Sample Size　177

  5-3.6　The Assumption of No Interaction in a Two-Factor Model　178

  5-3.7　One Observation per Cell　179

  5-4　The General Factorial Design　182

  5-5　Fitting Response Curves and Surfaces　188

  5-6　Blocking in a Factorial Design　193

  5-7　Problems　197

  Chapter 6　The 2k Factorial Design　203

  6-1　Introduction　203

  6-2　The 22 Design　204

  6-3　The 23 Design　211

  6-4　The General 2k Design　224

  6-5　A Single Replicate of the 2k Design　226

  6-6　The Addition of Center Points to the 2k Design　247

  6-7　Why We Work with Coded Design Variables　251

  6-8　Problems　254

  Chapter 7　Blocking and Confounding in the 2k Factorial Design　265

  7-1　Introduction　265

  7-2　Blocking a Replicated 2k Factorial Design　266

  7-3　Confounding in the 2k Factorial Design　266

  7-4　Confounding the 2k Factorial Design in Two Blocks　267

  7-5　Another Illustration of Why Blocking Is Important　273

  7-6　Confounding the 2k Factorial Design in Four Blocks　275

  7-7　Confounding the 2k Factorial Design in 2p Blocks　276

  7-8　Partial Confounding　278

  7-9　Problems　280

  Chapter 8　Two-Level Fractional Factorial Designs　282

  8-1　Introduction　282

  8-2　The One-Half Fraction of the 2k Design　283

  8-2.1　Definitions and Basic Principles　283

  8-2.2　Design Resolution　285

  8-2.3　Construction and Analysis of the One-Half Fraction　286

  8-3　The One-Quarter Fraction of the 2k Design　296

  8-4　The General 2k2p Fractional Factorial Design　303

  8-4.1　Choosing a Design　303

  8-4.2　Analysis of 2k2p Fractional Factorials　306

  8-4.3　Blocking Fractional Factorials　307

  8-5　Resolution III Designs　312

  8-5.1　Constructing Resolution III Designs　312

  8-5.2　Fold Over of Resolution III Fractions to Separate Aliased Effects　314

  8-5.3　PlackettDBurman Designs　319

  8-6　Resolution IV and V Designs　322

  8-6.1　Resolution IV Designs　322

  8-6.2　Sequential Experimentation with Resolution IV Designs　325

  8-6.3　Resolution V Designs　331

  8-7　Supersaturated Designs　333

  8-8　Summary　335

  8-9　Problems　335

  Chapter 9　Three-Level and Mixed-Level Factorial and Fractional Factorial Designs　347

  9-1　The 3k Factorial Design　347

  9-1.1　Notation and Motivation for the 3k Design　347

  9-1.2　The 32 Design　349

  9-1.3　The 33 Design　351

  9-1.4　The General 3k Design　355

  9-2　Confounding in the 3k Factorial Design　356

  9-2.1　The 3k Factorial Design in Three Blocks　356

  9-2.2　The 3k Factorial Design in Nine Blocks　360

  9-2.3　The 3k Factorial Design in 3p Blocks　360

  9-3　Fractional Replication of the 3k Factorial Design　361

  9-3.1　The One-Third Fraction of the 3k Factorial Design　361

  9-3.2　Other 3k2p Fractional Factorial Designs　364

  9-4　Factorials with Mixed Levels　365

  9-4.1　Factors at Two and Three Levels　366

  9-4.2　Factors at Two and Four Levels　367

  9-5　Problems　369

  Chapter 10　Fitting Regression Models　373

  10-1　Introduction 　373

  10-2　Linear Regression Models　374

  10-3　Estimation of the Parameters in Linear Regression Models　375

  10-4　Hypothesis Testing in Multiple Regression　388

  10-4.1　Test for Significance of Regression　388

  10-4.2　Tests on Individual Regression Coefficients and Groups of Coefficients　390

  10-5　Confidence Intervals in Multiple Regression　393

  10-5.1　Confidence Intervals on the Individual Regression Coefficients　393

  10-5.2　Confidence Interval on the Mean Response　394

  10-6　Prediction of New Response Observations　394

  10-7　Regression Model Diagnostics　396

  10-7.1　Scaled Residuals and PRESS　396

  10-7.2　Influence Diagnostics　399

  10-8　Testing for Lack of Fit　400

  10-9　Problems　401

  Chapter 11　Response Surface Methods and Designs　405

  11-1　Introduction to Response Surface Methodology　405

  11-2　The Method of Steepest Ascent　407

  11-3　Analysis of a Second-Order Response Surface　413

  11-3.1　Location of the Stationary Point　413

  11-3.2　Characterizing the Response Surface　415

  11-3.3　Ridge Systems　422

  11-3.4　Multiple Responses　423

  11-4　Experimental Designs for Fitting Response Surfaces　427

  11-4.1　Designs for Fitting the First-Order Model　428

  11-4.2　Designs for Fitting the Second-Order Model　428

  11-4.3　Blocking in Response Surface Designs　436

  11-4.4　Computer-Generated (Optimal) Designs　439

  11-5　Mixture Experiments　444

  11-6　Evolutionary Operation　452

  11-7　Problems　458

  Chapter 12　Robust Parameter Design and Process Robustness Studies　464

  12-1　Introduction　464

  12-2　Crossed Array Designs　466

  12-3　Analysis of the Crossed Array Design　468

  12-4　Combined Array Designs and the Response Model Approach　471

  12-5　Choice of Designs　477

  12-6　Problems　480

  Chapter 13　Experiments with Random Factors　484

  13-1　The Random Effects Model　485

  13-2　The Two-Factor Factorial with Random Factors　490

  13-3　The Two-Factor Mixed Model　495

  13-4　Sample Size Determination with Random Effects　500

  13-5　Rules for Expected Mean Squares　501

  13-6　Approximate F Tests　505

  13-7　Some Additional Topics on Estimation of Variance Components　511

  13-7.1　Approximate Confidence Intervals on Variance Components　511

  13-7.2　The Modified Large-Sample Method　514

  13-7.3　Maximum Likelihood Estimation of Variance Components　516

  13-8　Problems　521

  Chapter 14　Nested and Split-Plot Designs　525

  14-1　The Two-Stage Nested Design　525

  14-1.1　Statistical Analysis　526

  14-1.2　Diagnostic Checking　531

  14-1.3　Variance Components　532

  14-1.4　Staggered Nested Designs　533

  14-2　The General m-Stage Nested Design　534

  14-3　Designs with Both Nested and Factorial Factors　536

  14-4　The Split-Plot Design　540

  14-5　Other Variations of the Split-Plot Design　545

  14-5.1　Split-Plot Designs with More Than Two Factors　545

  14-5.2　The Split-Split-Plot Design　550

  14-5.3　The Strip-Split-Plot Design　552

  14-6　Problems　554

  Chapter 15　Other Design and Analysis Topics　559

  15-1　Nonnormal Responses and Transformations　560

  15-1.1　Selecting a Transformation: The BoxDCox Method　560

  15-1.2　The Generalized Linear Model　563

  15-2　Unbalanced Data in a Factorial Design　570

  15-2.1　Proportional Data: An Easy Case　571

  15-2.2　Approximate Methods　572

  15-2.3　The Exact Method　574

  15-3　The Analysis of Covariance　574

  15-3.1　Description of the Procedure　576

  15-3.2　Computer Solution　583

  15-3.3　Development by the General Regression Significance Test　584

  15-3.4　Factorial Experiments with Covariates　586

  15D4　Repeated Measures　590

  15-5　Problems　592

  Bibliography　595

  Appendix　603

  Table I.　Cumulative Standard Normal Distribution　604

  Table II.　Percentage Points of the t Distribution　606

  Table III.　Percentage Points of the x2 Distribution　607

  Table IV.　Percentage Points of the F Distribution　608

  Table V.　Operating Characteristic Curves for the Fixed Effects Model Analysis of Variance　613

  Table VI.　Operating Characteristic Curves for the Random Effects Model Analysis of Variance　617

  Table VII.　Percentage Points of the Studentized Range Statistic　621

  Table VIII.　Critical Values for Dunnett's Test for Comparing Treatments with a Control　623

  Table IX.　Coefficients of Orthogonal Polynomials　625

  Table X.　Alias Relationships for 2k-p Fractional Factorial Designs with k≤15 and n≤64　626

  Index　638