can do so only within a confidence interval of possible values. In addition to the inherent limitations of the measurement technique, a range of other factors may also be present and can affect the accuracy of laboratory analyses. Such factors may include deficiencies in the reference materials used in the analysis, equipment errors, environmental conditions that lie outside the range within which the method was validated, sample mix-ups and contamination, transcriptional errors, and more.

Consider, for example, a case in which an instrument (e.g., a breathalyzer such as Intoxilyzer) is used to measure the blood-alcohol level of an individual three times, and the three measurements are 0.08 percent, 0.09 percent, and 0.10 percent. The variability in the three measurements may arise from the internal components of the instrument, the different times and ways in which the measurements were taken, or a variety of other factors. These measured results need to be reported, along with a confidence interval that has a high probability of containing the true blood-alcohol level (e.g., the mean plus or minus two standard deviations). For this illustration, the average is 0.09 percent and the standard deviation is 0.01 percent; therefore, a two-standard-deviation confidence interval (0.07 percent, 0.11 percent) has a high probability of containing the person’s true blood-alcohol level. (Statistical models dictate the methods for generating such intervals in other circumstances so that they have a high probability of containing the true result.) The situation for assessing heroin content from a sample of white powder is similar, although the quantification and limits are not as broadly standardized. The combination of gas chromatography and mass spectrometry (GC/MS) is used extensively in identifying controlled substances. Those analyses tend to be more qualitative (e.g., identifying peaks on a spectrum that appear at frequencies consistent with the controlled substance and which stand out above the background “noise”), although quantification is possible.

Error Rates

Analyses in the forensic science disciplines are conducted to provide information for a variety of purposes in the criminal justice process. However, most of these analyses aim to address two broad types of questions: (1) can a particular piece of evidence be associated with a particular class of sources? and (2) Can a particular piece of evidence be associated with one particular source? The first type of question leads to “classification” conclusions. An example of such a question would be whether a particular hair specimen shares physical characteristics common to a particular ethnic group. An affirmative answer to a classification question indicates only that the item belongs to a particular class of similar items. Another example might be whether a paint mark left at a crime scene is consistent (according

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