Graphical Methods for the Design of Experiments
Nonfiction, Science & Nature, Mathematics, Statistics
| Author: | Russell R. Barton | ISBN: | 9781461213987 |
| Publisher: | Springer New York | Publication: | December 6, 2012 |
| Imprint: | Springer | Language: | English |
| Author: | Russell R. Barton |
| ISBN: | 9781461213987 |
| Publisher: | Springer New York |
| Publication: | December 6, 2012 |
| Imprint: | Springer |
| Language: | English |
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 tools that are useful for justifying the effort required for experimentation, identifying variables and candidate statistical models, 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 way that is easier to understand than a set of model coefficients. The text merely assumes a basic knowledge of statistics and matrices, while many of the graphical techniques are accessible without any knowledge of statistical models, requiring only some familiarity with the plotting of functions and with the concept of projection from elementary mechanical drawing.
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 tools that are useful for justifying the effort required for experimentation, identifying variables and candidate statistical models, 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 way that is easier to understand than a set of model coefficients. The text merely assumes a basic knowledge of statistics and matrices, while many of the graphical techniques are accessible without any knowledge of statistical models, requiring only some familiarity with the plotting of functions and with the concept of projection from elementary mechanical drawing.
