To describe the uncertainties of a standard test method, precision and bias statements are required. The formulation of these statements has been addressed from time to time, and at least two standards practices (Practices E177 and E691) have been issued. The 1986 Compilation of ASTM Standard Definitions (1) devotes several pages to these terms. This guide should not be used in cases where small numbers of test results do not support statistical normality.

ANSI N15.5 attempts to provide "a standard on statistical terminology and notation [that] can benefit communication" among nuclear materials managers. Precision, accuracy, and bias are all discussed. Although these various documents are quite valuable, a simpler document written for analysts appears needed. The intent of this guide is to help analysts prepare and interpret precision and bias statements. It is essential that, when the terms are used, their meaning should be clear and easily understood.

Appendix X1 provides the theoretical foundation for precision and bias concepts and Practice E691 addresses the problem of sources of variation. To illustrate the interplay between sources of variation and formulation of precision and bias statements, a hypothetical data set is analyzed in Appendix X2. This example shows that depending on how the data was collected, different precision and bias statements are possible. Reference to this example will be found throughout this guide.

There has been much debate inside and outside the statistical community on the exact meaning of some statistical terms. Thus, following a number of the terms in Section 3 is a list of several ways in which that term has been used. This listing is not meant to indicate that these meanings are equivalent or equally acceptable. The purpose here is more to encourage clear definition of terms used than to take sides. For example, use of the term systematic error is discouraged by some. If it is to be used, the reader should be told exactly what is meant in the particular circumstance.

This guide is intended as an aid to understanding the statistical concepts used in precision and bias statements. There is no intention that this be a self-contained introduction to statistics. Since many analysts have no formal statistical training, it is advised that a trained statistician be consulted for further clarification if necessary.