Statistical design is one of the fundamentals of our subject, being at the core of the growth of statistics during the previous century. Design played a key role in agricultural statistics and set down principles of good practic, principles that still apply today. Statistical design is all about understanding where the variance comes from, and making sure that is where the replication is. Indeed, it is probably correct to say that these principles are even more important today.
From the reviews: "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 important area. (Christine ANDERSON-COOK, JASA, June 2009, Vol. 104, No. 486) "The goal is to describe the principles that drive good design, which are also the principles that drive good statistics'. ! Casella succeeds exceptionally well to reach his goals. I greatly enjoyed browsing through this book. The author's experience and writing skills together make this an excellent course book. Concepts are presented in a very reader-friendly and instructive way. ! The layout of the book, huge amount of examples, and very clear writing make this a book highly recommended for anyone interested in statistical design." (Simo Puntanen, International Statistical Review, Vol. 76 (3), 2008) "Overall, I found reading this book to be worthwhile. I particularly think the author's discussion of blocking is quite interesting as well as the discussion of loop designs versus balanced incomplete block designs. In fact, I intend to use this book as supplementary reading material for my own design course." (Biometrics, December 2008)
Basics.- Completely randomized designs.- Complete block designs.- Interlude: assessing the effects of blocking.- Split plot designs.- Confounding in blocks.
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