Titlebook: Conference on Statistical Science Honouring the Bicentennial of Stefano Franscini’s Birth; Ascona November 18–2 Carlo Malaguerra,Stephan Mo

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Transdisziplin?re Jugendforschungally p quality characteristics are necessary for an adequate description of each item quality. Because of the inherent variability of a process, these quality characteristics are random variables. There are many causes of variability, but in statistical process control is useful to think of variabil

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https://doi.org/10.1007/978-3-531-92587-5om Kriege“, the first systematic and comprehensive treatment of the subject, published in 1832 after the author’s death. In data analysis, strategy is a relatively recent innovation. A decade ago, in a talk on ”Environments for supporting statistical strategy“ I had quipped that it was difficult to

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Measuring and Diagnosing the Efficiency of Electricity Services in Buildingsce turned out to be unsuitable, due to the wide diversity of common services in buildings. Therefore, the project was redirected towards the development of a complete set of partial electricity performance indicators: one for each type of common service.

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Control Charts for Multivariate Processes Based on Influence Functionsne methods for quality improvement where the influence function is used to build up control charts to monitor process variability and orientation. Our aim is to quickly detect the time when special causes are present in a manufacturing process, so investigation of the process and corrective actions

Fermentation

Transdisziplin?r und transformativ forschenrtage of statistical information about the subject forced Edmund Halley to obtain from Gottfried Leibniz data from the city of Breslau for his study (1693). Leibniz complied with Halley’s request and the German data sent to England has served for a long time (for well over a century) as the basis of

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Silent-Ischemia

Transdisziplin?re Jugendforschungne methods for quality improvement where the influence function is used to build up control charts to monitor process variability and orientation. Our aim is to quickly detect the time when special causes are present in a manufacturing process, so investigation of the process and corrective actions

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