The Analysis of Variance

1. Introduction.- 2. One-Way Classification.- 3. Two-Way Crossed Classification Without Interaction.- 4. Two-Way Crossed Classification With Interaction.- 5. Three-Way and Higher-Order Crossed Classifications.- 6. Two-Way Nested (Hierarchical) Classification.- 7. Three-Way and Higher-Order Nested Classifications.- 8. Partially Nested Classifications.- 9. Finite Population and Other Models.- 10. Some Simple Experimental Designs.- 11. Analysis of Variance Using Statistical Computing Packages.- Appendices.- B Chi-Square Distribution.- E Noncentral Chi-Square Distribution.- I Studentized Range Distribution.- J Studentized Maximum Modulus Distribution.- K Satterthwaite Procedure and Its Application to.- Analysis of Variance.- L Components of Variance.- M Intraclass Correlation.- N Analysis of Covariance.- Q Expected Value and Variance.- R Covariance and Correlation.- S Rules for Determining the Analysis of Variance Model.- T Rules for Calculating Sums of Squares and Degrees of Freedom.- U Rules for Finding Expected Mean Squares.- V Samples and Sampling Distribution.- W Methods of Statistical Inference.- X Some Selected Latin Squares.- Y Some Selected Graeco-Latin Squares.- Z PROC MIXED Outputs for Some Selected.- Worked Examples.- Statistical Tables and Charts.- Tables.- I Cumulative Standard Normal Distribution.- II Percentage Points of the Standard Normal Distribution.- IV Critical Values of the Chi-Square Distribution.- X Critical Values of the Studentized Range Distribution.- XI Critical Values of the Dunnett's Test.- XII Critical Values of the Duncan's Multiple Range Test.- XIV Critical Values of the Dunn-Sidák's Multiple Comparison Test.- XV Critical Values of the Studentized Maximum Modulus Distribution.- XVI Critical Values of the Studentized AugmentedRangeDistribution.- XVIII Coefficients of Order Statistics for the Shapiro-Wilk's W Test for Normality.- XIX Critical Values of the Shapiro-Wilk's W Test for Normality.- XXI Critical Values of the Bartlett's Test

"Intended as a text for an introductory analysis of variance service course, it requires little more than a precalculus understanding of probability, estimation, and hypothesis testing.... The student and practitioner will benefit from a well-balanced mixture of statistical theory, formulas, and explanations and the great care exercised by the authors in discussing properties and analysis of fixed, random, and mixed models in parallel.... The book employs several devices to aid readability.... In summary, the text is...a valuable source for the practitioner and nonstatistics major... It is well organized and well written at a difficulty level that precisely meets the target audience's needs."   -JASA