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摘要

Data analysis is a cornerstone of quality improvement. While there's obviously much more to quality than data and statistics, devoid of analytics, quality can devolve into a lot of hype, slogans and fanfare. This explains why quality professionals have effectively applied tools, such as statistical process control, experimental design and regression analysis, for decades.As data sets have gotten larger and easier to download from the internet, however, information about the quality of the data often is lost, assumed or overlooked. This situation shouldn't be surprising because the clear majority of statistics textbooks present every data set as a "random sample" of impeccable quality. It is, therefore, understandable that some quality professionals would assume that data are "innocent until proven guilty." Too often, they are not even under suspicion.