Optimal experimental design with R
 Responsibility
 Dieter Rasch ... [et al.].
 Language
 English.
 Imprint
 Boca Raton, FL : CRC Press, c2011.
 Physical description
 xix, 325 p. : ill. ; 25 cm.
Access
Creators/Contributors
 Contributor
 Rasch, Dieter.
Contents/Summary
 Bibliography
 Includes bibliographical references (p. 307317) and index.
 Contents

 Introduction Experimentation and empirical research Designing experiments Some basic definitions Block designs About the Rprograms Determining the Minimal Size of an Experiment for Given Precision Sample Size Determination in Completely Randomised Designs Introduction Confidence estimation Selection procedures Testing hypotheses Summary of sample size formulae Size of Experiments in Analysis of Variance Models Introduction Oneway layout Twoway layout Threeway layout Sample Size Determination in Model II of Regression Analysis Introduction Confidence intervals Hypothesis testing Selection procedures Sequential Designs Introduction Wald's sequential likelihood ratio test (SLRT) for oneparametric exponential families Test about means for unknown variances Triangular designs A sequential selection procedure Construction of Optimal Designs Constructing Balanced Incomplete Block Designs Introduction Basic definitions Construction of BIBD Constructing Fractional Factorial Designs Introduction and basic notations Factorial designs
 (source: Nielsen Book Data)
 Publisher's Summary
 Experimental design is often overlooked in the literature of applied and mathematical statistics: statistics is taught and understood as merely a collection of methods for analyzing data. Consequently, experimenters seldom think about optimal design, including prerequisites such as the necessary sample size needed for a precise answer for an experimental question. Providing a concise introduction to experimental design theory, Optimal Experimental Design with R: Introduces the philosophy of experimental design Provides an easy process for constructing experimental designs and calculating necessary sample size using R programs Teaches by example using a custom made R program package: OPDOE Consisting of detailed, datarich examples, this book introduces experimenters to the philosophy of experimentation, experimental design, and data collection. It gives researchers and statisticians guidance in the construction of optimum experimental designs using R programs, including sample size calculations, hypothesis testing, and confidence estimation. A final chapter of indepth theoretical details is included for interested mathematical statisticians.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2011
 Note
 "A Chapman & Hall book."
 ISBN
 9781439816974 (hbk. : acidfree paper)
 1439816972 (hbk. : acidfree paper)