Precision, Bias, and Accuracy
Accuracy is concerned with correctness. If a measurement process produces the correct results, it is accurate, and the measured value is also accurate. When closely scrutinized, repetitive measurements differ from one another and the means of sets will differ, however to a lesser degree. The scatter of the values is a measure of the precision; the less the scatter, the higher the precision. In a stable measurement process, a large number of individual values tend to converge toward a limiting mean, which may or may not be the true value. If not, the process is said to be biased. Measurement errors are of three types. Systematic errors are always of the same sign and magnitude and produce biases. Random errors vary in sign and magnitude and are unpredictable. Blunders are simply mistakes that occur on occasion and produce erroneous results. The analytical uncertainty must always be known when using data to make decisions.