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15.7: Chapter Summary and Key Terms

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    Few analyses are so straightforward that high quality results are obtained with ease. Good analytical work requires careful planning and an attention to detail. Creating and maintaining a quality assurance program is one way to help ensure the quality of analytical results. Quality assurance programs usually include elements of quality control and quality assessment.

    Quality control encompasses all activities used to bring a system into statistical control. The most important facet of quality control is written documentation, including statements of good laboratory practices, good measurement practices, standard operating procedures, and protocols for a specific purpose.

    Quality assessment includes the statistical tools used to determine whether an analysis is in a state of statistical control, and, if possible, to suggest why an analysis has drifted out of statistical control. Among the tools included in quality assessment are the analysis of duplicate samples, the analysis of blanks, the analysis of standards, and the analysis of spike recoveries.

    Another important quality assessment tool, which provides an ongoing evaluation of an analysis, is a control chart. A control chart plots a property, such as a spike recovery, as a function of time. Results that exceed warning and control limits, or unusual patterns of results indicate that an analysis is no longer under statistical control.

    Key Terms

    control chart
    good laboratory practices

    proficiency standard

    quality assurance program

    spike recovery

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    duplicate samples

    good measurement practices

    protocol for a specific purpose

    quality control

    standard operations procedure

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    quality assessment

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    statistical control

    This page titled 15.7: Chapter Summary and Key Terms is shared under a CC BY-NC-SA 4.0 license and was authored, remixed, and/or curated by David Harvey.

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