Abstract
This chapter focuses on the design of experiments, which is the process of planning and executing an experiment. It deals with the factorial experiments that are carried out within blocks, an analog of the multifactor analysis of variance (ANOVA), and classifies repeated measures designs by the number of between-subject and within-subject factors. The objective of an experimental design is to provide the maximum amount of reliable information at the minimum cost. The data resulting from the implementation of experimental designs are described by linear models and analyzed by the analysis of variance. One of the simplest and the most popular experimental design—the randomized block design—is described. In this design, the sample of experimental units is divided into groups or blocks and then treatments are randomly assigned to units in each block. The observations that come from within the same block have a natural matching mechanism. The data from a randomized block design can be described by a linear model that suggests the partitioning of the sum of squares and provides a justification for the test statistics.
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