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Six Sigma Hoax: The Way Professionals Deceive Science

机译:六西格码骗局:专业人士欺骗科学的方式

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Statistics is used in Physics (and in Nuclear Science as well): Six Sigma can be useful if properly applied; therefore scientists have to take into account the "correct" ideas. The document shows the ideas of the author to overcome the deep ignorance on Quality as it is found in many books dealing with Statistical Quality Control and Six Sigma. It is evident that there are many types of falseness provided by the "6 SigMONA practitioners": they rob money from their clients that are not aware of that. When the 6σ BMWists say "A company's performance is measured by the sigma level of their business processes" they lie: they do not know that, IF they compute s from the company's data, they know the estimate s (NOT σ) AND s is never equal to σ! The 1st falseness is the statement "variation is the enemy of Quality". The 2nd falseness is the statement "variability reduction is Quality". The 3rd falseness is the wide-spread use of the "Normal Distribution". The 4th falseness is the statement "the number of defectives is 3.4 ppm". The "6 SigMONA movement" does not deal properly with problem prevention, as on the contrary is done by GIQA. Scientificness is absent in the "6 SigMONA applications" as shown in the authors books.
机译:物理(以及核科学)中使用统计数据:如果正确应用六西格码可能会有用;因此,科学家必须考虑“正确”的想法。该文件显示了作者的想法,以克服对质量的深刻无知,这在许多涉及统计质量控制和六西格码的书籍中都可以找到。显然,“ 6名SigMONA从业者”提供了许多类型的虚假信息:他们从不知道这一点的客户那里抢钱。当6σBMW主义者说“公司的业绩是由其业务流程的sigma级别衡量的”时,他们说谎:他们不知道,如果他们从公司的数据中计算出s,他们就会知道估计值s(不是σ),而s是永远不等于σ!第一个错误是陈述“变化是质量的敌人”。第二个错误是陈述“减少可变性就是质量”。第三个错误是“正态分布”的广泛使用。第四个错误是陈述“缺陷数量为3.4 ppm”。 “ 6 SigMONA运动”不能正确地解决问题,而GIQA恰恰相反。如作者著作中所示,“ 6个SigMONA应用程序”中缺乏科学性。

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