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Design of Experiments—Factorial Designs

2004
Designs are often described by the number of factors. Chapter 6, “One-Way Analysis of Variance”, discusses designs with one factor. Chapter 12, “Two-Way Analysis of Variance”, discusses designs with two factors. More generally, we speak of “three-way” or “higher-way” designs and talk about main effects (one factor), two-way interactions (two factors ...
Richard M. Heiberger, Burt Holland
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Design of Experiments

2012
Design of experiments is introduced and its development from its birth within the statistics environment to its role in optimization is briefly described. Several DOE techniques are presented from a theoretical point of view after having introduced the terminology which is used in this field.
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Design of experiments

Journal of the Franklin Institute, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Design of Experiments

2020
Having an understanding of the factors that can bias or confound our experiments leads us to a consideration of the experimental design.
Michael Parkinson   +1 more
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Design of Experiments

1970
We shall discuss in this chapter some statistical methods for detecting changes in the response due to changes effected in the controllable variables assuming that the measurements are subject to random errors of measurement or changes in the unknown variables during the period of experimentation.
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Design of experiments

1980
In earlier chapters, I have discussed a very simple experiment on two treatments. In many practical situations, the subjects or materials fall naturally into groups, or can be organized as groups.
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Design of Experiment

2018
In the case of lack of theoretical knowledge of the relationships between input and outputs variables of a system, we have a second possibility: the experimental reconstruction of these relationships. In the case of theoretical knowledge, the system is represented by linear or nonlinear equations between input and output variables, while in the absence
Alessandro Freddi, Mario Salmon
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Design of Experiments

2009
Abstract After the failure analysis team hypothesizes failure causes, prepares a failure mode assessment and assignment, and evaluates all potential failure causes, it may find in some cases that several causes are still suspect but cannot be confirmed. In this situation, an experiment is necessary to confirm or rule out suspected causes.
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