{"product_id":"design-and-analysis-of-experiments-isbn-9781119722106","title":"Design and Analysis of Experiments","description":"\u003cp\u003e\u003ci\u003eDesign and Analysis of Experiments\u003c\/i\u003e provides a rigorous introduction to product and process design improvement through quality and performance optimization. Clear demonstration of widely practiced techniques and procedures allows readers to master fundamental concepts, develop design and analysis skills, and use experimental models and results in real-world applications. Detailed coverage of factorial and fractional factorial design, response surface techniques, regression analysis, biochemistry and biotechnology, single factor experiments, and other critical topics offer highly-relevant guidance through the complexities of the field.\u003c\/p\u003e \u003cp\u003eStressing the importance of both conceptual knowledge and practical skills, this text adopts a balanced approach to theory and application. Extensive discussion of modern software tools integrate data from real-world studies, while examples illustrate the efficacy of designed experiments across industry lines, from service and transactional organizations to heavy industry and biotechnology. Broad in scope yet deep in detail, this text is both an essential student resource and an invaluable reference for professionals in engineering, science, manufacturing, statistics, and business management.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eOC Content available in eBook\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSS Student solution available in interactive e-text\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003ePreface iii\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Strategy of Experimentation 1\u003c\/p\u003e \u003cp\u003e1.2 Some Typical Applications of Experimental Design 7\u003c\/p\u003e \u003cp\u003e1.3 Basic Principles 11\u003c\/p\u003e \u003cp\u003e1.4 Guidelines for Designing Experiments 13\u003c\/p\u003e \u003cp\u003e1.5 A Brief History of Statistical Design 19\u003c\/p\u003e \u003cp\u003e1.6 Summary: Using Statistical Techniques in Experimentation 20\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Simple Comparative Experiments 22\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 22\u003c\/p\u003e \u003cp\u003e2.2 Basic Statistical Concepts 23\u003c\/p\u003e \u003cp\u003e2.3 Sampling and Sampling Distributions 27\u003c\/p\u003e \u003cp\u003e2.4 Inferences About the Differences in Means, Randomized Designs 32\u003c\/p\u003e \u003cp\u003e2.4.1 Hypothesis Testing 32\u003c\/p\u003e \u003cp\u003e2.4.2 Confidence Intervals 38\u003c\/p\u003e \u003cp\u003e2.4.3 Choice of Sample Size 39\u003c\/p\u003e \u003cp\u003e2.4.4 The Case Where \u003ci\u003e𝜎\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e\u003csub\u003e1\u003c\/sub\u003e ≠ \u003ci\u003e𝜎\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e\u003csub\u003e2 \u003c\/sub\u003e43\u003c\/p\u003e \u003cp\u003e2.4.5 The Case Where \u003ci\u003e𝜎\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e\u003csub\u003e1 \u003c\/sub\u003eand \u003ci\u003e𝜎\u003csup\u003e2\u003c\/sup\u003e\u003c\/i\u003e\u003csub\u003e2 \u003c\/sub\u003eAre Known 45\u003c\/p\u003e \u003cp\u003e2.4.6 Comparing a Single Mean to a Specified Value 46\u003c\/p\u003e \u003cp\u003e2.4.7 Summary 47\u003c\/p\u003e \u003cp\u003e2.5 Inferences About the Differences in Means, Paired Comparison Designs 47\u003c\/p\u003e \u003cp\u003e2.5.1 The Paired Comparison Problem 47\u003c\/p\u003e \u003cp\u003e2.5.2 Advantages of the Paired Comparison Design 50\u003c\/p\u003e \u003cp\u003e2.6 Inferences About the Variances of Normal Distributions 52\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Experiments with a Single Factor: The Analysis of Variance 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 An Example 55\u003c\/p\u003e \u003cp\u003e3.2 The Analysis of Variance 58\u003c\/p\u003e \u003cp\u003e3.3 Analysis of the Fixed Effects Model 59\u003c\/p\u003e \u003cp\u003e3.3.1 Decomposition of the Total Sum of Squares 60\u003c\/p\u003e \u003cp\u003e3.3.2 Statistical Analysis 62\u003c\/p\u003e \u003cp\u003e3.3.3 Estimation of the Model Parameters 66\u003c\/p\u003e \u003cp\u003e3.3.4 Unbalanced Data 68\u003c\/p\u003e \u003cp\u003e3.4 Model Adequacy Checking 68\u003c\/p\u003e \u003cp\u003e3.4.1 The Normality Assumption 69\u003c\/p\u003e \u003cp\u003e3.4.2 Plot of Residuals in Time Sequence 71\u003c\/p\u003e \u003cp\u003e3.4.3 Plot of Residuals Versus Fitted Values 71\u003c\/p\u003e \u003cp\u003e3.4.4 Plots of Residuals Versus Other Variables 76\u003c\/p\u003e \u003cp\u003e3.5 Practical Interpretation of Results 76\u003c\/p\u003e \u003cp\u003e3.5.1 A Regression Model 77\u003c\/p\u003e \u003cp\u003e3.5.2 Comparisons Among Treatment Means 78\u003c\/p\u003e \u003cp\u003e3.5.3 Graphical Comparisons of Means 78\u003c\/p\u003e \u003cp\u003e3.5.4 Contrasts 79\u003c\/p\u003e \u003cp\u003e3.5.5 Orthogonal Contrasts 82\u003c\/p\u003e \u003cp\u003e3.5.6 Scheffé’s Method for Comparing All Contrasts 83\u003c\/p\u003e \u003cp\u003e3.5.7 Comparing Pairs of Treatment Means 85\u003c\/p\u003e \u003cp\u003e3.5.8 Comparing Treatment Means with a Control 88\u003c\/p\u003e \u003cp\u003e3.6 Sample Computer Output 89\u003c\/p\u003e \u003cp\u003e3.7 Determining Sample Size 93\u003c\/p\u003e \u003cp\u003e3.7.1 Operating Characteristic and Power Curves 93\u003c\/p\u003e \u003cp\u003e3.7.2 Confidence Interval Estimation Method 94\u003c\/p\u003e \u003cp\u003e3.8 Other Examples of Single-Factor Experiments 95\u003c\/p\u003e \u003cp\u003e3.8.1 Chocolate and Cardiovascular Health 95\u003c\/p\u003e \u003cp\u003e3.8.2 A Real Economy Application of a Designed Experiment 97\u003c\/p\u003e \u003cp\u003e3.8.3 Discovering Dispersion Effects 99\u003c\/p\u003e \u003cp\u003e3.9 The Random Effects Model 101\u003c\/p\u003e \u003cp\u003e3.9.1 A Single Random Factor 101\u003c\/p\u003e \u003cp\u003e3.9.2 Analysis of Variance for the Random Model 102\u003c\/p\u003e \u003cp\u003e3.9.3 Estimating the Model Parameters 103\u003c\/p\u003e \u003cp\u003e3.10 The Regression Approach to the Analysis of Variance 109\u003c\/p\u003e \u003cp\u003e3.10.1 Least Squares Estimation of the Model Parameters 110\u003c\/p\u003e \u003cp\u003e3.10.2 The General Regression Significance Test 111\u003c\/p\u003e \u003cp\u003e3.11 Nonparametric Methods in the Analysis of Variance 113\u003c\/p\u003e \u003cp\u003e3.11.1 The Kruskal–Wallis Test 113\u003c\/p\u003e \u003cp\u003e3.11.2 General Comments on the Rank Transformation 114\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Randomized Blocks, Latin Squares, and Related Designs 115\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 The Randomized Complete Block Design 115\u003c\/p\u003e \u003cp\u003e4.1.1 Statistical Analysis of the RCBD 117\u003c\/p\u003e \u003cp\u003e4.1.2 Model Adequacy Checking 125\u003c\/p\u003e \u003cp\u003e4.1.3 Some Other Aspects of the Randomized Complete Block Design 125\u003c\/p\u003e \u003cp\u003e4.1.4 Estimating Model Parameters and the General Regression Significance Test 130\u003c\/p\u003e \u003cp\u003e4.2 The Latin Square Design 133\u003c\/p\u003e \u003cp\u003e4.3 The Graeco-Latin Square Design 140\u003c\/p\u003e \u003cp\u003e4.4 Balanced Incomplete Block Designs 142\u003c\/p\u003e \u003cp\u003e4.4.1 Statistical Analysis of the BIBD 143\u003c\/p\u003e \u003cp\u003e4.4.2 Least Squares Estimation of the Parameters 147\u003c\/p\u003e \u003cp\u003e4.4.3 Recovery of Interblock Information in the BIBD 149\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Introduction to Factorial Designs 152\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Basic Definitions and Principles 152\u003c\/p\u003e \u003cp\u003e5.2 The Advantage of Factorials 155\u003c\/p\u003e \u003cp\u003e5.3 The Two-Factor Factorial Design 156\u003c\/p\u003e \u003cp\u003e5.3.1 An Example 156\u003c\/p\u003e \u003cp\u003e5.3.2 Statistical Analysis of the Fixed Effects Model 159\u003c\/p\u003e \u003cp\u003e5.3.3 Model Adequacy Checking 164\u003c\/p\u003e \u003cp\u003e5.3.4 Estimating the Model Parameters 167\u003c\/p\u003e \u003cp\u003e5.3.5 Choice of Sample Size 169\u003c\/p\u003e \u003cp\u003e5.3.6 The Assumption of No Interaction in a Two-Factor Model 170\u003c\/p\u003e \u003cp\u003e5.3.7 One Observation per Cell 171\u003c\/p\u003e \u003cp\u003e5.4 The General Factorial Design 174\u003c\/p\u003e \u003cp\u003e5.5 Fitting Response Curves and Surfaces 179\u003c\/p\u003e \u003cp\u003e5.6 Blocking in a Factorial Design 188\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 The 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 194\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 194\u003c\/p\u003e \u003cp\u003e6.2 The 2\u003csup\u003e2\u003c\/sup\u003e Design 195\u003c\/p\u003e \u003cp\u003e6.3 The 2\u003csup\u003e3\u003c\/sup\u003e Design 203\u003c\/p\u003e \u003cp\u003e6.4 The General 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 215\u003c\/p\u003e \u003cp\u003e6.5 A Single Replicate of the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 218\u003c\/p\u003e \u003cp\u003e6.6 Additional Examples of Unreplicated 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesigns 231\u003c\/p\u003e \u003cp\u003e6.7 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesigns are Optimal Designs 243\u003c\/p\u003e \u003cp\u003e6.8 The Addition of Center Points to the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 248\u003c\/p\u003e \u003cp\u003e6.9 Why We Work with Coded Design Variables 253\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Blocking and Confounding in the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e\u003c\/i\u003e Factorial Design 256\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 256\u003c\/p\u003e \u003cp\u003e7.2 Blocking a Replicated 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 256\u003c\/p\u003e \u003cp\u003e7.3 Confounding in the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 259\u003c\/p\u003e \u003cp\u003e7.4 Confounding the 2\u003ci\u003e\u003csup\u003ek \u003c\/sup\u003e\u003c\/i\u003eFactorial Design in Two Blocks 259\u003c\/p\u003e \u003cp\u003e7.5 Another Illustration of Why Blocking is Important 267\u003c\/p\u003e \u003cp\u003e7.6 Confounding the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design in Four Blocks 268\u003c\/p\u003e \u003cp\u003e7.7 Confounding the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design in 2\u003ci\u003e\u003csup\u003ep\u003c\/sup\u003e \u003c\/i\u003eBlocks 270\u003c\/p\u003e \u003cp\u003e7.8 Partial Confounding 271\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Two-Level Fractional Factorial Designs 274\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 274\u003c\/p\u003e \u003cp\u003e8.2 The One-Half Fraction of the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 275\u003c\/p\u003e \u003cp\u003e8.2.1 Definitions and Basic Principles 275\u003c\/p\u003e \u003cp\u003e8.2.2 Design Resolution 278\u003c\/p\u003e \u003cp\u003e8.2.3 Construction and Analysis of the One-Half Fraction 278\u003c\/p\u003e \u003cp\u003e8.3 The One-Quarter Fraction of the 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 290\u003c\/p\u003e \u003cp\u003e8.4 The General 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e\u003c\/i\u003e\u003csup\u003e−\u003ci\u003ep\u003c\/i\u003e\u003c\/sup\u003eFractional Factorial Design 297\u003c\/p\u003e \u003cp\u003e8.4.1 Choosing a Design 297\u003c\/p\u003e \u003cp\u003e8.4.2 Analysis of 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e\u003c\/i\u003e\u003csup\u003e−\u003ci\u003ep\u003c\/i\u003e\u003c\/sup\u003eFractional Factorials 300\u003c\/p\u003e \u003cp\u003e8.4.3 Blocking Fractional Factorials 301\u003c\/p\u003e \u003cp\u003e8.5 Alias Structures in Fractional Factorials and Other Designs 306\u003c\/p\u003e \u003cp\u003e8.6 Resolution III Designs 308\u003c\/p\u003e \u003cp\u003e8.6.1 Constructing Resolution III Designs 308\u003c\/p\u003e \u003cp\u003e8.6.2 Fold Over of Resolution III Fractions to Separate Aliased Effects 310\u003c\/p\u003e \u003cp\u003e8.6.3 Plackett–Burman Designs 313\u003c\/p\u003e \u003cp\u003e8.7 Resolution IV and V Designs 322\u003c\/p\u003e \u003cp\u003e8.7.1 Resolution IV Designs 322\u003c\/p\u003e \u003cp\u003e8.7.2 Sequential Experimentation with Resolution IV Designs 323\u003c\/p\u003e \u003cp\u003e8.7.3 Resolution V Designs 329\u003c\/p\u003e \u003cp\u003e8.8 Supersaturated Designs 329\u003c\/p\u003e \u003cp\u003e8.9 Summary 331\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Additional Design and Analysis Topics for Factorial and Fractional Factorial Designs 332\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 The 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 333\u003c\/p\u003e \u003cp\u003e9.1.1 Notation and Motivation for the 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 333\u003c\/p\u003e \u003cp\u003e9.1.2 The 3\u003csup\u003e2\u003c\/sup\u003e Design 334\u003c\/p\u003e \u003cp\u003e9.1.3 The 3\u003csup\u003e3\u003c\/sup\u003e Design 335\u003c\/p\u003e \u003cp\u003e9.1.4 The General 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eDesign 340\u003c\/p\u003e \u003cp\u003e9.2 Confounding in the 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 340\u003c\/p\u003e \u003cp\u003e9.2.1 The 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design in Three Blocks 340\u003c\/p\u003e \u003cp\u003e9.2.2 The 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design in Nine Blocks 343\u003c\/p\u003e \u003cp\u003e9.2.3 The 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design in 3\u003ci\u003e\u003csup\u003ep\u003c\/sup\u003e \u003c\/i\u003eBlocks 344\u003c\/p\u003e \u003cp\u003e9.3 Fractional Replication of the 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 345\u003c\/p\u003e \u003cp\u003e9.3.1 The One-Third Fraction of the 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e \u003c\/i\u003eFactorial Design 345\u003c\/p\u003e \u003cp\u003e9.3.2 Other 3\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e\u003c\/i\u003e\u003csup\u003e−\u003ci\u003ep\u003c\/i\u003e\u003c\/sup\u003eFractional Factorial Designs 348\u003c\/p\u003e \u003cp\u003e9.4 Factorials with Mixed Levels 349\u003c\/p\u003e \u003cp\u003e9.4.1 Factors at Two and Three Levels 349\u003c\/p\u003e \u003cp\u003e9.4.2 Factors at Two and Four Levels 351\u003c\/p\u003e \u003cp\u003e9.5 Nonregular Fractional Factorial Designs 352\u003c\/p\u003e \u003cp\u003e9.5.1 Nonregular Fractional Factorial Designs for 6, 7, and 8 Factors in 16 Runs 354\u003c\/p\u003e \u003cp\u003e9.5.2 Nonregular Fractional Factorial Designs for 9 Through 14 Factors in 16 Runs 362\u003c\/p\u003e \u003cp\u003e9.5.3 Analysis of Nonregular Fractional Factorial Designs 368\u003c\/p\u003e \u003cp\u003e9.6 Constructing Factorial and Fractional Factorial Designs Using an Optimal Design Tool 369\u003c\/p\u003e \u003cp\u003e9.6.1 Design Optimality Criterion 370\u003c\/p\u003e \u003cp\u003e9.6.2 Examples of Optimal Designs 370\u003c\/p\u003e \u003cp\u003e9.6.3 Extensions of the Optimal Design Approach 378\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Fitting Regression Models 382\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 382\u003c\/p\u003e \u003cp\u003e10.2 Linear Regression Models 383\u003c\/p\u003e \u003cp\u003e10.3 Estimation of the Parameters in Linear Regression Models 384\u003c\/p\u003e \u003cp\u003e10.4 Hypothesis Testing in Multiple Regression 395\u003c\/p\u003e \u003cp\u003e10.4.1 Test for Significance of Regression 395\u003c\/p\u003e \u003cp\u003e10.4.2 Tests on Individual Regression Coefficients and Groups of Coefficients 397\u003c\/p\u003e \u003cp\u003e10.5 Confidence Intervals in Multiple Regression 399\u003c\/p\u003e \u003cp\u003e10.5.1 Confidence Intervals on the Individual Regression Coefficients 400\u003c\/p\u003e \u003cp\u003e10.5.2 Confidence Interval on the Mean Response 400\u003c\/p\u003e \u003cp\u003e10.6 Prediction of New Response Observations 401\u003c\/p\u003e \u003cp\u003e10.7 Regression Model Diagnostics 402\u003c\/p\u003e \u003cp\u003e10.7.1 Scaled Residuals and PRESS 402\u003c\/p\u003e \u003cp\u003e10.7.2 Influence Diagnostics 405\u003c\/p\u003e \u003cp\u003e10.8 Testing for Lack of Fit 405\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Response Surface Methods and Designs 408\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction to Response Surface Methodology 408\u003c\/p\u003e \u003cp\u003e11.2 The Method of Steepest Ascent 411\u003c\/p\u003e \u003cp\u003e11.3 Analysis of a Second-Order Response Surface 416\u003c\/p\u003e \u003cp\u003e11.3.1 Location of the Stationary Point 416\u003c\/p\u003e \u003cp\u003e11.3.2 Characterizing the Response Surface 418\u003c\/p\u003e \u003cp\u003e11.3.3 Ridge Systems 424\u003c\/p\u003e \u003cp\u003e11.3.4 Multiple Responses 425\u003c\/p\u003e \u003cp\u003e11.4 Experimental Designs for Fitting Response Surfaces 430\u003c\/p\u003e \u003cp\u003e11.4.1 Designs for Fitting the First-Order Model 430\u003c\/p\u003e \u003cp\u003e11.4.2 Designs for Fitting the Second-Order Model 430\u003c\/p\u003e \u003cp\u003e11.4.3 Blocking in Response Surface Designs 437\u003c\/p\u003e \u003cp\u003e11.4.4 Optimal Designs for Response Surfaces 440\u003c\/p\u003e \u003cp\u003e11.5 Experiments with Computer Models 454\u003c\/p\u003e \u003cp\u003e11.6 Mixture Experiments 461\u003c\/p\u003e \u003cp\u003e11.7 Evolutionary Operation 472\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Robust Parameter Design and Process Robustness Studies 477\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 477\u003c\/p\u003e \u003cp\u003e12.2 Crossed Array Designs 479\u003c\/p\u003e \u003cp\u003e12.3 Analysis of the Crossed Array Design 481\u003c\/p\u003e \u003cp\u003e12.4 Combined Array Designs and the Response Model Approach 484\u003c\/p\u003e \u003cp\u003e12.5 Choice of Designs 490\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Experiments with Random Factors 493\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Random Effects Models 493\u003c\/p\u003e \u003cp\u003e13.2 The Two-Factor Factorial with Random Factors 494\u003c\/p\u003e \u003cp\u003e13.3 The Two-Factor Mixed Model 500\u003c\/p\u003e \u003cp\u003e13.4 Rules for Expected Mean Squares 505\u003c\/p\u003e \u003cp\u003e13.5 Approximate \u003ci\u003eF\u003c\/i\u003e-Tests 508\u003c\/p\u003e \u003cp\u003e13.6 Some Additional Topics on Estimation of Variance Components 512\u003c\/p\u003e \u003cp\u003e13.6.1 Approximate Confidence Intervals on Variance Components 512\u003c\/p\u003e \u003cp\u003e13.6.2 The Modified Large-Sample Method 516\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Nested and Split-Plot Designs 518\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 The Two-Stage Nested Design 518\u003c\/p\u003e \u003cp\u003e14.1.1 Statistical Analysis 519\u003c\/p\u003e \u003cp\u003e14.1.2 Diagnostic Checking 524\u003c\/p\u003e \u003cp\u003e14.1.3 Variance Components 526\u003c\/p\u003e \u003cp\u003e14.1.4 Staggered Nested Designs 526\u003c\/p\u003e \u003cp\u003e14.2 The General \u003ci\u003em\u003c\/i\u003e-Stage Nested Design 528\u003c\/p\u003e \u003cp\u003e14.3 Designs with Both Nested and Factorial Factors 530\u003c\/p\u003e \u003cp\u003e14.4 The Split-Plot Design 534\u003c\/p\u003e \u003cp\u003e14.5 Other Variations of the Split-Plot Design 540\u003c\/p\u003e \u003cp\u003e14.5.1 Split-Plot Designs with More Than Two Factors 540\u003c\/p\u003e \u003cp\u003e14.5.2 The Split-Split-Plot Design 545\u003c\/p\u003e \u003cp\u003e14.5.3 The Strip-Split-Plot Design 549\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Other Design and Analysis Topics (Available in e-text for students) W-1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eProblems P-1\u003c\/p\u003e \u003cp\u003eAppendix A-1\u003c\/p\u003e \u003cp\u003eTable I. Cumulative Standard Normal Distribution A-2\u003c\/p\u003e \u003cp\u003eTable II. Percentage Points of the \u003ci\u003et \u003c\/i\u003eDistribution A-4\u003c\/p\u003e \u003cp\u003eTable III. Percentage Points of the \u003ci\u003e𝜒 \u003c\/i\u003e\u003csup\u003e2\u003c\/sup\u003e Distribution A-5\u003c\/p\u003e \u003cp\u003eTable IV. Percentage Points of the \u003ci\u003eF \u003c\/i\u003eDistribution A-6\u003c\/p\u003e \u003cp\u003eTable V. Percentage Points of the Studentized Range Statistic A-11\u003c\/p\u003e \u003cp\u003eTable VI. Critical Values for Dunnett’s Test for Comparing Treatments with a Control A-13\u003c\/p\u003e \u003cp\u003eTable VII. Coefficients of Orthogonal Polynomials A-15\u003c\/p\u003e \u003cp\u003eTable VIII. Alias Relationships for 2\u003ci\u003e\u003csup\u003ek\u003c\/sup\u003e\u003c\/i\u003e\u003csup\u003e−\u003ci\u003ep\u003c\/i\u003e\u003c\/sup\u003eFractional Factorial Designs with \u003ci\u003ek \u003c\/i\u003e≤ 15 and \u003ci\u003en \u003c\/i\u003e≤ 64 A-16\u003c\/p\u003e \u003cp\u003eOC Bibliography (Available in e-text for students) B-1\u003c\/p\u003e \u003cp\u003eIndex I-1\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989043003621,"sku":"NP9781119722106","price":141.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119722106.jpg?v=1761782557","url":"https:\/\/k12savings.com\/products\/design-and-analysis-of-experiments-isbn-9781119722106","provider":"K12savings","version":"1.0","type":"link"}