# ASTM E2655-14(R2020) pdf free download

ASTM E2655-14(R2020) pdf free download.Standard Guide for Reporting Uncertainty of Test Results and Use of the Term Measurement Uncertainty in ASTM Test Methods

5. Concepts for Reporting Uncertainty of Test Results

5.1 Uncertainty is part of the relationship of a test result to the property of interest for the material tested. When a test procedure is applied to a material, the test result is a value for a characteristic of the material. The test result obtained will usually differ from the actual value for that material. Multiple causes can contribute to the error of result. Errors of sampling and effects ofsample handling make the portion actually tested not identical to the material as a whole. Imperfections in the test apparatus and its calibration, environmental, and human factors also affect the result of testing. Nonetheless, after testing has been completed, the result obtained will be used for further purposes as if it were the actual value. Reporting measurement uncertainty for a test result is an attempt to estimate the approximate magnitude of all these sources of error. In common cases the measurement will be reported in the form x 6 u, in which x represents the test result and u represents the uncertainty associated with x. 5.2 Practice E177 describes precision and bias. Uncertainty is a closely related but not identical concept. The primary difference between concepts of precision and of uncertainty is the object that they address. Precision (repeatability and reproducibility) and bias are attributes ofthe test method. They are estimates of statistical variability of test results for a test method applied to a given material. Repeatability and interme- diate precision measure variation within a laboratory. Repro- ducibility refers to interlaboratory variation. Uncertainty is an attribute of the particular test result for a test material. It is an estimate of the quality of that particular test result.5.3 In the case of a quantity with a definition that does not depend on the measurement or test method (for example, concentration, pH, modulus, heat content), uncertainty mea- sures how close it is believed the measured value comes to the quantity. For results of test methods where the target is only definable relative to the test method (for example, flash points, extractable components, sieve analysis), uncertainty of a test result must be interpreted as a measure of how closely an independent, equally competent test result would agree with that being reported. 5.4 In the simplest cases, uncertainty of a test result is numerically equivalent to test method precision. That is, if an unknown sample is tested, and the test precision is known to be sigma, then uncertainty of the result of test is sigma. The term uncertainty, however, is correct to apply where variation of repeated test results is not relevant, as in the following examples.

5.6 A commonly cited definition (2, 3) defines uncertainty as “a parameter, associated with the measurement result, or test result, that characterizes the dispersion of values that could reasonably be attributed to the quantity subject to measurement or characteristic subject to test.” This definition emphasizes uncertainty as an attribute ofthe particular result, as opposed to statistical variation of test results. The uncertainty parameter is a measure of spread (for example, the standard deviation) of a probability distribution used to represent the likelihood of values of the property. 5 5.7 The methodology for uncertainty estimates has been classified as Type A and Type B as discussed in (4). Type A estimates of uncertainty include standard error estimates based on knowledge of the statistical character of observations, and based on statistical analysis of replicate measurements. Type B estimates of uncertainty include approximate values derived from experience with measurement processes similar to the one being considered, and estimates of standard uncertainty de- rived from the range of possible measurement values for a given material and an assumed distribution of values within that range. See Practice E122 for examples (for example, rectangular, triangular, normal) where a standard deviation is derived from a range without data from samples being avail- able. Complex estimates of test result uncertainty are calcu- lated by combining Type A and Type B component standard uncertainties for factors contributing to error (see Section 8).