Analysis of Variance, Design, and Regression: Applied Statistical Methods

Abstract

Preface Introduction One Sample A General Theory for Testing and Confidence Intervals Two Sample Problems One-Way Analysis of Variance Multiple Comparison Methods Simple Linear and Polynomial Regression The Analysis of Count Data Basic Experimental Designs Analysis of Covariance Factorial Treatment Structures Split Plots, Repeated Measures, Random Effects, and Subsampling Multiple Regression: Matrix Formation Unbalanced Multifactor Analysis of Variance Confounding and Fractional Replication in 2n Factorial Systems Nonlinear Regression Appendix A: Matrices Appendix B: Tables References Author Index Subject Index

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