Results 231 to 240 of about 167,868,153 (286)

Design of Experiments in Statistics

2000
Models and Information Matrix. Most of the results in experimental design theory are related to the linear regression models: $$ E\{ y|x\} = \eta ({\theta ^T},x) and Var\{ y|x\} = \sigma 2(x), $$ (17.1.1) where the observation y is a random variable, E and Var stand for expectation and variance, respectively.
Valerii Fedorov, Jon Lee
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Design of Experiments: Statistical Principles of Research Design and Analysis

Technometrics, 2001
(2001). Design of Experiments: Statistical Principles of Research Design and Analysis. Technometrics: Vol. 43, No. 2, pp. 236-237.
Mark Anderson, Patrick Whitcomb
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History of the Statistical Design of Agricultural Experiments

Journal of Agricultural, Biological and Environmental Statistics, 2020
In Section 1 the approach of improving crop yields by the development of agriculture and addition of various mineral or organic substances in the last 200–300 years is investigated. In Section 2 the principle of randomized experiments is treated. Section 3 describes the variety trials of field crops.
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Statistical databases: Design of experiment structures

Information Systems, 1993
Abstract This paper discusses some special data patterns in relational databases, which are characteristics of the design and analysis of statistical experiments. First, we introduce the concept of order of functional independence in relational tables to provide a formal definition for relational data structure for statistical paired samples. We then
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Statistical Design of Experiments (DoE)

2021
In a cause–effect relationship, the design of experiments (DoE) is a means and method of determining the interrelationship in the required accuracy and scope with the lowest possible expenditure in terms of time, material, and other resources. In experiments, the question concerning which type and level of effect the influencing variables have on the ...
Hartmut Schiefer, Felix Schiefer
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Statistical Principles for the Design of Experiments

2012
This book is about the statistical principles behind the design of effective experiments and focuses on the practical needs of applied statisticians and experimenters engaged in design, implementation and analysis. Emphasising the logical principles of statistical design, rather than mathematical calculation, the authors demonstrate how all available ...
R. Mead, S. G. Gilmour, A. Mead
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Statistical Design and Analysis of Experiments

Technometrics, 1972
Sidney Addelman, Peter W. M. John
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Design and Analysis of Statistical Experiments

2001
Statistical Experimental Design (SED), also referred to as Design of Experiments (DoE), is a valuable tool in reliability assessment. When properly set up and executed, designed experiments can serve to identify principal factors contributing to product unreliability or identify key factors on which to apply improvement and corrective action resources ...
John W. Evans, Jillian Y. Evans
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Statistical Design of Fatigue Experiments

Journal of Applied Mechanics, 1952
Abstract An analytical expression connecting fatigue lives with applied stresses, and methods for computing the values of its parameters from experimental data are given. Formulas for estimating the uncertainty of computed parameter values, caused by scatter of loads and fatigue lives, for optimum distribution of specimens, and for ...
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Statistical Design and Analysis of Experiments

1996
A problem solving strategy employing experimental designs is illustrated in optimizing the yield of a secondary metabolite in solid substrate culture. The strategy employs a screening Plackett-Burman design that selects two of six factors. Then a two- level factorial design is carried out in order to define a search direction.
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