Graphical methods have played an important role in the statistical analysis of experimental data, but have not been used as extensively for experiment design, at least as it is presented in most design of experiments texts. Yet graphical methods are particularly attractive for the design of experiments because they exploit our creative right-brain capabilities. Creative activity is clearly important in any kind of design, certainly for the design ofan experiment. The experimenter must somehow select a set of run conditions that will meet the goals for a particular experiment in a cost-efficient way. Graphical Methods for Experiment Design goes beyond graphical methods for choosing run conditions for an experiment. It looks at the entire pre-experiment planning process, and presents in one place a collection of graphical methods for defining experiment goals, identifying and classifying variables, for choosing a model, for developing a design, and for assessing the adequacy of a design for estimating the unknown coefficients in the proposed statistical model. In addition, tools for developing a design also provide a platform for viewing the results of the experiment, a platform that provides insights that cannot be obtained by examination ofregression coefficients. These techniques can be applied to a variety of situations, including experimental runs of computer simulation models. Factorial and fractional-factorial designs are the focus of the graphical representations, although mixture experiments and experiments involving random effects and blocking are designed and represented in similar ways.
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1 Introduction.- The role of experiment design in statistical methodology.- The five main steps in the design of an experiment.- Summary of topics.- The videodisk pressing example.- Study questions.- 2 Planning for a Designed Experiment.- Goal hierarchy plots.- Individual experiment goals and form of the statistical model.- Experiment goals: other aspects.- Key terms in experiment design.- Identifying and classifying variables.- Choosing a model: a priori main effect and interaction plots.- Summary.- Study questions.- 3 Design-Plots for Factorial and Fractional-Factorial Designs.- Factorial designs.- Graphical presentation of factorial designs.- Factorial designs and corresponding regression models.- Graphical projections and the notion of effect sparsity.- Confounding in fractional-factorial designs.- Geometric patterns of confounding relations.- Design-plots for other designs.- Study questions.- 4 Designing Experiments Graphically.- Constructing two-level fractional-factorial designs.- Designing fractional-factorial experiments with three or more levels.- Videodisk pressing example.- Graphical design of mixture experiments.- Graphical designs for blocking and nested effects.- Confounding graphs.- Experiment designs for robust design.- Designing pilot experiments.- Study questions.- 5 Assessing Experiment Designs.- A videodisk experiment design.- Numerical measures for design assessment.- Design assessment and `optimal’ designs.- Graphical methods for assessing confounding in regular 2k-pdesigns.- Prediction error plots.- Designs for a manufacturing simulation study.- Shaded-block matrix plots.- Parallel coordinate plots.- A model with dependent random perturbations.- Study questions.- 6 Presenting Results Graphically.- Traditional graphical displays of experimental results.- Response-scaled design-plots.- Constructing a response-scaled design-plot.- Interpreting response-scaled design-plots.- Response-scaled design-plots and robust design.- Model-free interpretation of experimental results.- Study questions.
Book by Barton Russell R
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The design of experiments is recognized as a critical activity in scientific investigations and industrial quality management programs, but many texts on the design of experiments focus on the analysis of experimental data, not the creation of the design. Graphical Methods for Experimental Design presents a strategic view of the planning of experiments, and provides a number of graphical tools that are useful for justifying the effort required for experimentation, for identifying variables and candidate statistical models, for selecting the set of run conditions and for assessing the quality of the design. In addition, the graphical framework for creating fractional factorial designs is used to present experimental results in a fashion that can be easier to understand than a set of model coefficients. The text assumes a basic knowledge of statistics and matrices. Many of the graphical techniques are accessible without any knowledge of statistical models however, requiring only some familiarity with the plotting of functions and with the concept of projection from elementary mechanical drawing. 212 pp. Englisch. Codice articolo 9780387947501
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Most texts on the design of experiments focus on the analysis of experimental data, not on the creation of the design. Graphical Methods for Experimental Design presents a strategic view of the planning of experiments, and provides a number of graphical too. Codice articolo 5912174
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Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Graphical methods have played an important role in the statistical analysis of experimental data, but have not been used as extensively for experiment design, at least as it is presented in most design of experiments texts. Yet graphical methods are particularly attractive for the design of experiments because they exploit our creative right-brain capabilities. Creative activity is clearly important in any kind of design, certainly for the design ofan experiment. The experimenter must somehow select a set of run conditions that will meet the goals for a particular experiment in a cost-efficient way. Graphical Methods for Experiment Design goes beyond graphical methods for choosing run conditions for an experiment. It looks at the entire pre-experiment planning process, and presents in one place a collection of graphical methods for defining experiment goals, identifying and classifying variables, for choosing a model, for developing a design, and for assessing the adequacy of a design for estimating the unknown coefficients in the proposed statistical model. In addition, tools for developing a design also provide a platform for viewing the results of the experiment, a platform that provides insights that cannot be obtained by examination ofregression coefficients. These techniques can be applied to a variety of situations, including experimental runs of computer simulation models. Factorial and fractional-factorial designs are the focus of the graphical representations, although mixture experiments and experiments involving random effects and blocking are designed and represented in similar ways. Codice articolo 9780387947501
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Graphical methods have played an important role in the statistical analysis of experimental data, but have not been used as extensively for experiment design, at least as it is presented in most design of experiments texts. Yet graphical methods are particularly attractive for the design of experiments because they exploit our creative right-brain capabilities. Creative activity is clearly important in any kind of design, certainly for the design ofan experiment. The experimenter must somehow select a set of run conditions that will meet the goals for a particular experiment in a cost-efficient way. Graphical Methods for Experiment Design goes beyond graphical methods for choosing run conditions for an experiment. It looks at the entire pre-experiment planning process, and presents in one place a collection of graphical methods for defining experiment goals, identifying and classifying variables, for choosing a model, for developing a design, and for assessing the adequacy of a design for estimating the unknown coefficients in the proposed statistical model. In addition, tools for developing a design also provide a platform for viewing the results of the experiment, a platform that provides insights that cannot be obtained by examination ofregression coefficients. These techniques can be applied to a variety of situations, including experimental runs of computer simulation models. Factorial and fractional-factorial designs are the focus of the graphical representations, although mixture experiments and experiments involving random effects and blocking are designed and represented in similar ways.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 212 pp. Englisch. Codice articolo 9780387947501
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