Elementary Statistical Methods and Measurement Error. - Vardeman, Stephen B.; Wendelberger, Joanne R.; Burr, Tom; Hamada, Michael S.; Moore, Leslie M.; Jobe, J. Marcus; Morris, Max D.; Wu, Huaiqing (American Statistician, 2010)
The way in which sources of physical variation interact with a data collection plan decides what can be learned from the resulting dataset, and how measurement error is reflected in the dataset especially. Implications of this fact are not usually given sufficient attention in the majority of statistics courses. Even the most basic statistical methods have their practical effectiveness curtailed by measurement variation; and comprehending how measurement variation interacts with data collection and the methods is useful for quantifying the nature of measurement error. The writers highlight how straightforward one- and two-sample statistical methods can be effectively used in introducing important concepts of metrology and the effects of those concepts when reaching conclusions on the basis of data.