Optimal experimental design with R
- Boca Raton, FL : CRC Press, c2011.
- Physical description
- xix, 325 p. : ill. ; 25 cm.
QA279 .O668 2011
- Unknown QA279 .O668 2011
- Rasch, Dieter.
- Includes bibliographical references (p. 307-317) and index.
- Introduction Experimentation and empirical research Designing experiments Some basic definitions Block designs About the R-programs 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 One-way layout Two-way layout Three-way 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 one-parametric 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, data-rich 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 in-depth theoretical details is included for interested mathematical statisticians.
(source: Nielsen Book Data)
- Publication date
- Dieter Rasch ... [et al.].
- "A Chapman & Hall book."
- 9781439816974 (hbk. : acid-free paper)
- 1439816972 (hbk. : acid-free paper)