Search results for: experimental-design

Engineering Quality and Experimental Design

Author : Daniel Michael Grove
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Keeping formulae to a minimum, the authors explain the fundamental ideas involved in planning efficient experiments and making good use of the results. Their strategies are inspired by the Japanese engineer Genichi Taguchi, but they show how many of Taguchi's objectives can be accomplished using simpler methods and modern computer technology. Annotation copyright by Book News, Inc., Portland, OR

Foundations of Optimum Experimental Design

Author : Andrej Pázman
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Introductory remarks about the experiment and its disign. The regression model and methods of estimation. The ordering of designs and the properties of variaces of estimates. Optimality critaria in the regression model. Iterative computation of optimum desings Design of experiments in particular cases. The functional model and measurements of physical fields.

Fundamenttals of Experimental Design

Author : Jerome L. Myers
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Statistics and Experimental Design for Toxicologists and Pharmacologists Fourth Edition

Author : Shayne C. Gad
File Size : 84.15 MB
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Purposefully designed as a resource for practicing and student toxicologists, Statistics and Experimental Design for Toxicologists and Pharmacologists, Fourth Edition equips you for the regular statistical analysis of experimental data. Starting with the assumption of basic mathematical skills and knowledge, the author supplies a complete and systematic yet practical introduction to the statistical methodologists available for, and used in, the discipline. For every technique presented, a worked example from toxicology is also presented. See what's new in the Fourth Edition: The first practical guide to performing meta analysis allowing for using the power inherent in multiple similar studies Coverage of Bayesian analysis and data analysis in pharmacology and toxicology Almost 200 problems with solutions Discussion of analysis of receptor binding assays, safety pharmacology assays and other standard types conducted in pharmacology A new chapter explaining the basics of Good Laboratory Practices (GLPs) For those with computer skills, this edition has been enhanced with the addition of basic SAS Written specifically for toxicologists and pharmacologists, the author draws on more than 30 years of experience to provide understanding of the philosophical underpinnings for the overall structure of analysis. The book's organization fosters the ordered development of skills and yet still facilitates ease of access to information as needed. This Fourth Edition gives you the tools necessary to perform rigorous and critical analysis of experimental data and the insight to know when to use them.

Research Animals and Experimental Design in Nephrology

Author : Hilmar Stolte
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Error robust Statistical Experimental Design with Application to Model based Sampling in Auditing

Author : Young-Il Kim
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A Multi model Bayesian Resampling Sequential Experimental Design for Response Surface Estimation

Author : David Leib Ledersnaider Dornbusch
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Advances in Quasi Experimental Design and Analysis

Author : William M. K. Trochim
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The intent of this volume of New Directions for Program Evaluation is to update, even to alter, our thinking about quasi-experimentation in applied social research and program evaluation. This volume makes the case that we have moved beyond the traditional thinking on quasi-experiments as a collection of specific designs and threats to validity toward a more integrated, synthetic view of quasi-experimentation as part of a general logical epistemological framework for research. This is the 31st issue of New Directions for Program Evaluation. For more information on the series, please see the Journals and Periodicals page.

Improving Experimental Design and Statistical Inference for Transcriptional Profiling Experiments

Author : Juan Pedro Steibel
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Statistics and Experimental Design for Behavioral and Biological Researchers

Author : Victor H. Denenberg
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What statistics is all about; Measurement: the choice of an endpoint; Descriptive statistics: frequency curves, averages, and variability; Making inferences about population parameters: general principles; The normal curve; The distribution; Comparing the means of an experimental and a control group; The analysis of variance: single classification; The analysis of variance: nested designs randomized blocks, and factorial experiments; Determining the linear relationship between variables: the correlation coefficient; Chi-square tests of nominal data; Order statistics for ranked data.