Includes bibliographical references and index.

Strategy of Experimentation -- Some Typical Applications of Experimental Design -- Guidelines for Designing Experiments -- A Brief History of Statistical Design -- Summary: Using Statistical Techniques in Experimentation -- Simple Comparative Experiments -- Basic Statistical Concepts -- Sampling and Sampling Distributions -- Inferences About the Differences in Means, Randomized Designs -- Hypothesis Testing -- Choice of Sample Size -- Confidence Intervals -- The Case Where [sigma superscript 2 subscript 1] [not equal] [sigma superscript 2 subscript 2] -- The Case Where [sigma superscript 2 subscript 1] and [sigma superscript 2 subscript 2] Are Known -- Comparing a Single Mean to a Specified Value -- Inferences About the Differences in Means, Paired Comparison Designs -- The Paired Comparison Problem -- Advantages of the Paired Comparison Design -- Inferences About the Variances of Normal Distributions -- Experiments with a Single Factor: The Analysis of Variance -- The Analysis of Variance -- Analysis of the Fixed Effects Model -- Decomposition of the Total Sum of Squares -- Statistical Analysis -- Estimation of the Model Parameters -- Unbalanced Data -- Model Adequacy Checking -- The Normality Assumption -- Plot of Residuals in Time Sequence -- Plot of Residuals Versus Fitted Values -- Plots of Residuals Versus Other Variables -- Practical Interpretation of Results -- A Regression Model -- Comparisons Among Treatment Means -- Graphical Comparisons of Means -- Contrasts -- Orthogonal Contrasts -- Scheffe's Method for Comparing All Contrasts -- Comparing Pairs of Treatment Means -- Comparing Treatment Means with a Control -- Sample Computer Output -- Determining Sample Size -- Operating Characteristic Curves -- Specifying a Standard Deviation Increase -- Confidence Interval Estimation Method -- Discovering Dispersion Effects -- The Regression Approach to the Analysis of Variance -- Least Squares Estimation of the Model Parameters -- The General Regression Significance Test -- Nonparametric Methods in the Analysis of Variance -- The Kruskal--Wallis Test -- General Comments on the Rank Transformation -- Randomized Blocks, Latin Squares, and Related Designs -- The Randomized Complete Block Design -- Statistical Analysis of the RCBD -- Model Adequacy Checking -- Some Other Aspects of the Randomized Complete Block Design -- Estimating Model Parameters and the General Regression Significance Test -- The Latin Square Design -- The Graeco--Latin Square Design -- Balanced Incomplete Block Designs -- Statistical Analysis of the BIBD -- Least Squares Estimation of the Parameters -- Recovery of Interblock Information in the BIBD -- Introduction to Factorial Designs -- Basic Definitions and Principles -- The Advantage of Factorials -- The Two-Factor Factorial Design -- Statistical Analysis of the Fixed Effects Model -- Model Adequacy Checking -- Estimating the Model Parameters -- Choice of Sample Size -- The Assumption of No Interaction in a Two-Factor Model -- One Observation per Cell -- The General Factorial Design -- Fitting Response Curves and Surfaces -- Blocking in a Factorial Design -- The 2[superscript k] Factorial Design -- The 2[superscript 2] Design -- The 2[superscript 3] Design -- The General 2[superscript k] Design -- A Single Replicate of the 2[superscript k] Design -- The Addition of Center Points to the 2[superscript k] Design -- Blocking and Confounding in the 2[superscript k] Factorial Design -- Blocking a Replicated 2[superscript k] Factorial Design -- Confounding in the 2[superscript k] Factorial Design -- Confounding the 2[superscript k] Factorial Design in Two Blocks -- Confounding the 2[superscript k] Factorial Design in Four Blocks -- Confounding the 2[superscript k] Factorial Design in 2[superscript p] Blocks -- Partial Confounding -- Two-Level Fractional Factorial Designs -- The One-Half Fraction of the 2[superscript k] design -- The One-Quarter Fraction of the 2[superscript k] Design -- The General 2[superscript k-p] Fractional Factorial Design -- Resolution III Designs -- Resolution IV and V Designs -- Three-Level and Mixed-Level Factorial and Fractional Factorial Designs -- The 3[superscript k] Factorial Design -- Notation and Motivation for the 3[superscript k] Design -- The 3[superscript 2] Design -- The 3[superscript 3] Design -- The General 3[superscript k] design -- Confounding in the 3[superscript k] Factorial Design -- The 3[superscript k] Factorial Design in Three Blocks -- The 3[superscript k] Factorial Design in Nine Blocks -- The 3[superscript k] Factorial Design in 3[superscript p] Blocks -- Fractional Replication of the 3[superscript k] Factorial Design -- The One-Third Fraction of the 3[superscript k] Factorial Design -- Other 3[superscript k-p] Fractional Factorial Designs -- Factorials with Mixed Levels -- Factors at Two and Three Levels -- Factors at Two and Four Levels -- Fitting Regression Models -- Linear Regression Models -- Estimation of the Parameters in Linear Regression Models -- Hypothesis Testing in Multiple Regression -- Test for Significance of Regression -- Tests on Individual Regression Coefficients and Groups of Coefficients -- Confidence Intervals in Multiple Regression -- Confidence Intervals on the Individual Regression Coefficients -- Confidence Interval on the Mean Response -- Prediction of New Response Observations -- Regression Model Diagnostics -- Scaled Residuals and PRESS -- Influence Diagnostics -- Testing for Lack of Fit -- Response Surface Methods and Other Approaches to Process Optimization -- Introduction to Response Surface Methodology -- The Method of Steepest Ascent -- Analysis of a Second-Order Response Surface -- Location of the Stationary Point -- Characterizing the Response Surface -- Ridge Systems -- Multiple Responses -- Experimental Designs for Fitting Response Surfaces -- Designs for Fitting the First-Order Model -- Designs for Fitting the Second-Order Model -- Blocking in Response Surface Designs -- Computer-Generated (Optimal) Designs -- Mixture Experiments -- Evolutionary Operation -- Robust Design -- The Response Surface Approach to Robust Design -- Experiments with Random Factors -- The Random Effects Model -- The Two-Factor Factorial with Random Factors -- The Two-Factor Mixed Model -- Sample Size Determination with Random Effects -- Rules for Expected Mean Squares -- Approximate F Tests -- Some Additional Topics on Estimation of Variance Components -- Approximate Confidence Intervals on Variance Components -- The Modified Large-Sample Method -- Maximum Likelihood Estimation of Variance Components -- Nested and Split-Plot Designs -- The Two-Stage Nested Design -- Statistical Analysis -- Diagnostic Checking -- Variance Components -- Staggered Nested Designs -- The General m-Stage Nested Design -- Designs with Both Nested and Factorial Factors -- The Split-Plot Design -- Other Variations of the Split-Plot Design -- Split-Plot Designs with More Than Two Factors -- The Split-Split-Plot Design -- The Strip-Split-Plot Design -- Other Design and Analysis Topics -- Nonnormal Responses and Transformations -- Selecting a Transformation: The Box-Cox Method -- The Generalized Linear Model -- Unbalanced Data in a Factorial Design -- Proportional Data: An Easy Case -- Approximate Methods -- The Exact Method -- The Analysis of Covariance -- Description of the Procedure -- Computer Solution -- Development by the General Regression Significance Test -- Factorial Experiments with Covariates -- Repeated Measures -- Cumulative Standard Normal Distribution -- Percentage Points of the t Distribution -- Percentage Points of the x[superscript 2] Distribution -- Percentage Points of the F Distribution -- Operating Characteristic Curves for the Fixed Effects Model Analysis of Variance -- Operating Characteristic Curves for the Random Effects Model Analysis of Variance -- Significant Ranges for Duncan's Multiple Range Test -- Percentage Points of the Studentized Range Statistic -- Critical Values for Dunnett's Test for Comparing Treatments with a Control -- Coefficients of Orthogonal Polynomials -- Random Numbers -- Alias Relationships for 2[superscript k-p] Fractional Factorial Designs with k [less than or equal] 15 and n [less than or equal] 64.