Demonstrating the Consistency of Small Data Sets: Application of the Weisberg t-test for Outliers
May 15th 2003by Robert J. Seely, Amgen, Inc. Louis Munyakazi, John Haury, Heather Simmerman, W. Heath Rushing, and Thomas F. Curry Determining whether a data point is an "outlier" ? a result that doesn't fit, that is too high or too low, that is extreme or discordant ? is difficult when using small data sets (such as the data from three, four, or five conformance runs). The authors show that the Weisberg t-test is a powerful tool for detecting deviations in small data sets.
Statistical Tools for Setting In-Process Acceptance Criteria
October 15th 2001by Robert J. Seely, Louis Munyakazi, and John Haury Regulatory approval and successful manufacturing depend on establishing meaningful and reasonable acceptance criteria for process validations and ongoing monitoring. Three methods are presented here to correct for the likely underestimation of process limits due to small samples.