By implementing calibration procedures, control samples, and appropriate adjustments, the impact of systematic errors can be minimized, leading to more precise and accurate results.
To detect systematic errors in an analytical method, the following paired statements are true:
True: A systematic error is consistent and predictable, affecting all measurements in the same way.
False: A random error is unpredictable and can vary from one measurement to another.
True: Systematic errors can be identified through calibration procedures and control samples.
False: Random errors are typically assessed using statistical methods and replicate measurements.
True: Systematic errors can be corrected or minimized through calibration adjustments and method improvements.
False: Random errors cannot be eliminated entirely, but their impact can be reduced by increasing the number of replicate measurements.
True: Systematic errors lead to biased results that consistently deviate from the true value.
False: Random errors cause imprecision and result in scatter or variability around the true value.
It is important to identify and address systematic errors in analytical methods to ensure accurate and reliable measurements.
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