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Method Blank
- A blank prepared to represent the sample matrix as closely
as possible and analyzed exactly like the calibration standards, samples, and
quality control (QC) samples. Results of method blanks provide an estimate
of the within-batch variability of the blank response and an indication of
bias introduced by the analytical procedure.
Trip Blank
- A clean sample of a matrix that is taken to the sampling site
and transported to the laboratory for analysis without having been exposed
to sampling procedures
.
Chain of Custody
- An unbroken trail of accountability that ensures the physical security of samples,
data, and records.
Comparability
- A measure of the confidence with which one data set or method can be compared to
another.
Completeness
- A measure of the amount of valid data obtained from a measurement system compared to
the amount that was expected to be obtained under correct, normal conditions.
Data Quality Assessment (DQA)
- The scientific and statistical evaluation of data to determine if data
obtained from environmental operations are of the right type, quality, and quantity to support their
intended use. The five steps of the DQA Process include: 1) reviewing the DQOs and sampling design, 2)
conducting a preliminary data review, 3) selecting the statistical test, 4) verifying the assumptions of the
statistical test, and 5) drawing conclusions from the data
Data Quality Indicators (DQIs)
- The quantitative statistics and qualitative descriptors that are used to
interpret the degree of acceptability or utility of data to the user. The principal data quality indicators are
bias, precision, accuracy (bias is preferred), comparability, completeness, representativeness. DQIs
provide a metric against which the performance of a program can be measured during the implementation
and/or assessment phases of a verification test
.
Data Quality Objectives (DQOs)
- The qualitative and quantitative statements derived from the DQO
Process that clarify study’s technical and quality objectives, define the appropriate type of data, and
specify tolerable levels of potential decision errors that will be used as the basis for establishing the
quality and quantity of data needed to support decisions.
Data Quality Objectives (DQO) Process
- A systematic strategic planning tool that identifies and
defines the type, quality, and quantity of data needed to satisfy a specified use. DQOs are the qualitative
and quantitative outputs from the DQO Process.
Data Validation
- A procedure for assessing whether or not a set of data have met acceptability criteria
defined in the data quality objective process.
Detection Limit (DL)
- A measure of the capability of an analytical method to distinguish samples that
do not contain a specific analyte from samples that contain low concentrations of the analyte; the lowest
concentration or amount of the target analyte that can be determined to be different from zero by a single
measurement at a stated level of probability. DLs are analyte- and matrix-specific and may be laboratory-
dependent. Some of the more commonly used definitions are:
Instrument Detection Limit (IDL)
- The lowest concentration or mass an instrument can detect
above background instrument noise under ideal conditions. Sample preparation is not considered
in the determination of an IDL.