Overview

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.

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9780387523224

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<p>From the reviews: <p> In an era where many design texts present a wide collection of tools and practical considerations for creating designs, this book is a marked contrast with a primary focus on developing a thorough understanding of the core of design theory. The book is an excellent reference for those already familiar with design of experiments, because of its careful and detailed presentation of core designs and how to verify that an appropriate analysis is chosen to match the structure of how the data were collected. In addition it contains numerous nuggets of wisdom about potential pitfalls from inattention to detail. Overall, the style of the book gives a clear, understandable presentation of the formal details of statistical design for many core design types for balanced data involving categorical factors. The mathematical detail and rigor of the text allows students the opportunity to form a firm foundation on which to build their understanding and intuition about this

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