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• W1036654834 abstract "The application of statistical experimental design and optimization (SEDOP) to environmental chemistry research is presented. The use of SEDOP approaches for environmental research has the potential to increase the amount of information and the reliability of results, at a cost comparable to, or lower than, traditional approaches. We demonstrate how researchers can attain these benefits by adhering to a systematic program of design and execution of experiments, including the analysis and interpretation of results. The lack of general knowledge about experimental statistical techniques had hindered their widespread application in the environmental field. To benefit from the SEDOP advantages, the United States Environmental Protection Agency (USEPA) has an ongoing project to investigate applications of statistical design to environmental chemistry problems. There exist standard experimental arrangements (designs) to address all phases of a research program, from identifying important effects, to modeling the behavior of the experimental system of interest, to optimizing the operating conditions (e.g., minimizing waste or maximizing reproducibility). The most useful standard design arrangements (both for system characterization and optimization) are introduced, together with a discussion of their applicability to pollutant analysis as well as their strengths and weaknesses. Practical environmental applications from the literature are presented and discussed from the perspective of the approaches and techniques that they illustrate. Examples include optimization of analyte extraction, instrument calibration, method comparison, ruggedness testing, selection of indicator contaminants, and pollution prevention. The implementation of statistical experimental design today is greatly facilitated by the use of available software for the selection of designs, the planning of experiments, the analysis of data, and the graphical presentation of results." @default.
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• W1036654834 date "1995-01-01" @default.
• W1036654834 modified "2023-09-23" @default.
• W1036654834 title "Experimental Design and Optimization" @default.
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• W1036654834 doi "https://doi.org/10.1007/978-3-540-49148-4_3" @default.
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