Design and Analysis of Experiments

This comprehensive text presents classical and regression approaches to experimental design and analysis. Capitalizing on the availability of cutting-edge software, the author uses both manual methods and SAS programs to carry out analyses. He provides examples to illustrate numerous designs, such as randomized complete block, Latin square, GraecoLatin square, and balanced incomplete block designs. The text includes the full SAS code and outputs as well as end-of-chapter exercises to encourage hands-on SAS programming experience. A solutions manual is available upon qualified course adoption.

Unlike other books on the modeling and analysis of experimental data, Design and Analysis of Experiments: Classical and Regression Approaches with SAS not only covers classical experimental design theory, it also explores regression approaches. Capitalizing on the availability of cutting-edge software, the author uses both manual methods and SAS programs to carry out analyses.

The book presents most of the different designs covered in a typical experimental design course. It discusses the requirements for good experimentation, the completely randomized design, the use of orthogonal contrast to test hypotheses, and the model adequacy check. With an emphasis on two-factor factorial experiments, the author analyzes repeated measures as well as fixed, random, and mixed effects models. He also describes designs with randomization restrictions, before delving into the special cases of the 2^k and 3^k factorial designs, including fractional replication and confounding. In addition, the book covers response surfaces, balanced incomplete block and hierarchical designs, ANOVA, ANCOVA, and MANOVA.

Fortifying the theory and computations with practical exercises and supplemental material, this distinctive text provides a modern, comprehensive treatment of experimental design and analysis.

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