Statistical Design

Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. This book covers the basic theoretical underpinnings. It describes the principles that drive good designs and good statistics.

Covers both theory and application of designs, from agriculture to microarrays Examples and Exercises taken from real experiments, with data on the web and illustrative R programs Theoretical details are contained in Technical Notes sections Includes supplementary material: sn.pub/extras

Klappentext

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.

Inhalt
Basics.- Completely Randomized Designs.- Complete Block Designs.- Interlude: Assessing the Effects of Blocking.- Split Plot Designs.- Confounding in Blocks.