All quantitative measurements have a degree of measurement uncertainty. While the term uncertainty can be essentially defined as doubt, measurement uncertainty in this sense instead inspires assurance in a quantitative value to a certain degree of confidence. Dating back to the advent of modern statistics in the 1700s, an international consensus on measurement uncertainty did not occur until the 1995 release of the Guide to the Expression of Uncertainty in Measurement (GUM), the fundamental document on the subject. The GUM was further adopted by major players in the field of measurement including the International Bureau of Weights and Measures (BIPM), National Measurement Institutes (NMI), and the International Organization for Standardization (ISO), and is used as the gold standard of documentary standards in labs around the country.
Gunshot residue (GSR) patterns of distribution are used to establish a range of possible distances that the muzzle of the firearm was from the target in order to piece together a particular series of events. Using the firearm and ammunition that was involved in that particular crime, an analyst can perform test fires using fabric swatches attached to test panels at varying muzzle-to-target distances, generally every three to six inches between contact and 48 inches. This allows for the creation of comparable patterns of soot and GSR to the actual pieces of evidence. Because different distances can have considerably different residue patterns, it is important that a method for creating the test panels minimize uncertainty in order to be considered reliable and reproducible. When establishing a protocol for determining the measurement uncertainty in the creation of test panels, the two most important factors are the measuring device and a repeatability study. A measuring device, in this case a stainless-steel ruler, with metrological traceability reduces the measurement uncertainty because every value is reliable and traceable back to an original source. A repeatability study is then used to take numerous measurements over time under similar conditions. Using this data, statistical analysis can be applied to evaluate the standard deviations and uncertainties.
A total of 238 measurements were taken by eight members of the Boston Police Department Crime Laboratory on eleven different days over the course of a month. The measurements were divided into eight baseline distances that the firing device, a Ransom Rest, had been set to: 3”, 6”, 9”, 12”, 18”, 24”, 36”, and 42”. The data was analyzed as a whole, as well as split into two groups: a group of four analysts who are proficient and authorized to perform GSR distance determination testing (Group A), and a second group of four analysts with no GSR distance determination training or experience (Group B). At a confidence interval of 95.45%, the reported uncertainty was found to be 0.082 inches for the total group, 0.045 inches for the group trained in performing GSR distance determination, and 0.043 inches for the group with no experience in distance determination testing. F-test statistical analysis of the standard deviations of each distance, along with a comparison of the uncertainties, indicates no significant difference between the abilities of the two groups and that it’s possible a new uncertainty of measurement will not be required when current GSR distance determination analysts leave or new analysts are hired and trained, given that all other variables remain constant.
The outlined method and experiment for determining measurement uncertainty was successful in that it met the four main requirements set forward by the American National Standards Institute (ANSI) National Accreditation Board (ANAB): (a) include the specific measuring device or instrument used for a reported test result in the estimation of measurement uncertainty for that test method; (b) include the process of rounding the expanded uncertainty; (c) require the coverage probability of the expanded uncertainty to be a minimum of 95.45%; and (d) specify a schedule to review and/or recalculate the measurement uncertainty.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/36163 |
| Date | 11 June 2019 |
| Creators | Caldwell, Mikayla Marie |
| Contributors | Brodeur, Amy |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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