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Computing Statistics under Interval and Fuzzy Uncertainty Rutilius Taurus Aemilianus dass auf Fach- und Führungskräfte

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Computing Statistics under Interval and Fuzzy Uncertainty Rutilius Taurus Aemilianus dass auf Fach- und FührungskräfteIn many practical situations, we are interested in statistics characterizing a population of objects: e. g. in the mean height of people from a certain area. Most algorithms for estimating such statistics assume that the sample values are exact. In practice, sample values come from measurements, and measurements are never absolutely accurate. Sometimes, we know the exact probability distribution of the measurement inaccuracy, but often, we only know

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