Why is there so much emphasis on low and high outliers?
RESPONSE: Bulletin 17B does not explain this very well. It lumps a number of distinct problems and phenomena under the label “outlier,” but does not give much explanation of how the Bulletin-17-B conception of outliers differs from the classical concepts developed in the literature on statistics and analysis of measurement data. Bulletin 17-B defines outliers as data points that depart significantly from the trend of the remaining data when plotted as a frequency curve on magnitude-probability coordinates. By implication, outliers are data points that interfere with the fitting of simple trend curves to the data and, unless properly accounted for, are likely to cause simple fitted trend curves to grossly misrepresent the data. This definition is quite nebulous, furnishes little concrete guidance, and may be confusing to those unfamiliar with flood frequency analysis. However, flood data sets often do not conform to common statistical probability distributions and often contain observat
