Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693)
DOI: 10.1109/wsc.2003.1261436
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Crystal Ball for Six Sigma Tutorial

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Cited by 4 publications
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“…The number of parameters will vary from distribution to distribution; for instance, the mean and the variance have to be estimated for the normal distribution, while the uniform distribution requires estimates of the minimum and maximum values for the variable (Ragsdale, 2004) . Ultimately the pdf's size, shape, location, and dispersion parameters affect the range of values that the input may use during each iteration of the simulation model (Goldman and Emmett, 2003) .…”
Section: Fig 1 Multi-value Probability Distributionsmentioning
confidence: 99%
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“…The number of parameters will vary from distribution to distribution; for instance, the mean and the variance have to be estimated for the normal distribution, while the uniform distribution requires estimates of the minimum and maximum values for the variable (Ragsdale, 2004) . Ultimately the pdf's size, shape, location, and dispersion parameters affect the range of values that the input may use during each iteration of the simulation model (Goldman and Emmett, 2003) .…”
Section: Fig 1 Multi-value Probability Distributionsmentioning
confidence: 99%
“…Pessimistic and optimistic scenarios are usually presented. Useful though, the analysis can show only the range of outcomes, but not the probability of their occurrence (Goldman and Emmett, 2003) .…”
Section: Introductionmentioning
confidence: 99%
“…Představme si call centrum s nepřetržitým provozem, které smluvně pro velkou průmys-lovou fi rmu zajišťuje péči o zákazníky (Goldman, Emmett, 2003). Cílem je snížení počtu hovorů s dobou čekání nad 20 sekund, neboť se vyskytly stížnosti na dlouhé čekání na operátora a podle smlouvy za každé čekání nad dobu 20 sekund platí call centrum fi rmě smluvenou pokutu.…”
Section: Příklad Projektu Six Sigmaunclassified