Description
This text stands apart from other books on experiment design. It presents theory and methods, emphasizes both the design selection for an experiment and the analysis of data, and integrates the analysis for the various designs with the general theory for linear models. It begins with a general introduction to the subject, then leads readers through the theoretical results, the various design models, and the analytical concepts that provide the techniques that enable analysis of virtually any design. Rife with examples and exercises, the text also encourages using computers to analyze data. It features the SAS software package, but also demonstrates how any regression program can be used for analysis. With its clear, highly readable style, A First Course in the Design of Experiments proves ideal as both a reference and a text. TOC:Introduction to the Design of Experiments.- Definition of a Linear Model.- Least Squares Estimation and Normal Equations.- Linear Model Distribution Theory.- Distribution Theory for Statistical Inference.- Inference for Multiple Regression Models.- The Completely Randomized Design.- Planned Comparisons.- Multiple Comparisons.- Randomized Complete Block Design.- Incomplete Block Designs.- Latin Square Designs.- Factorial Experiments with Two Factors.- Analysis of Covariance.- Random and Mixed Models.- Nested Designs and Associated Topics.- Other Designs and Topics.- Appendix A: Matrix Algebra.- Appendix B: Tables.- References.- Index.
