3.3: Accuracy, Precision, and Error
- Page ID
- 42430
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Quality Control Standards
Quality control standards are samples prepared with a known amount of analyte. The purpose of these standards is to determine if the laboratory methods and equipment are capable of making accurate and precise measurements. These standards are important indicators of quality and provide instantaneous feedback on method and equipment performance.
Accuracy and Bias
Accuracy is the degree of closeness to the actual value. The goal of sample testing is to find the sample's true measured value for water quality parameters.
Bias is the systematic or persistent error in an analysis that results in the expected sample measurement being consistently different than the sample's true value. Bias results from a flaw integral to the testing system. Systematic bias will lead to systematic errors that skew high or low, as opposed to random errors, which generally cancel each other out.
An incorrectly calibrated home thermostat may consistently read several degrees hotter or colder than the actual temperature. This is an example of bias that commonly leads to systematic errors.
Precision
Precision is a measure of how closely multiple determinations performed on the same sample will agree with each other. Performing a test on a sample many times and measuring the same result each time is an example of precision. This does not mean, however, that the measured result is accurate. Systemic bias does not affect precision like it does accuracy.
Error
Error is the difference between the measurement and the true value. Error is expected in many experiments, even if it is a very small amount. To account for these small errors, uncertainty values are set to indicate a range of values, based on the measurement, that the true value will be in.