Although statistical design is one of the oldest branches of statistics,
its importance is ever increasing, especially in the face of the data
flood that often faces statisticians. It is important to recognize the
appropriate design, and to understand how to effectively implement it,
being aware that the default settings from a computer package can easily
provide an incorrect analysis. The goal of this book is to describe the
principles that drive good design, paying attention to both the
theoretical background and the problems arising from real experimental
situations. Designs are motivated through actual experiments, ranging
from the timeless agricultural randomized complete block, to microarray
experiments, which naturally lead to split plot designs and balanced
incomplete blocks.