What is the difference between accuracy & precision?


Accuracy: it is the degree of closeness with which an instrumentation reading approaches to the true value of
the quantity being measured.

Precision: it is a measure of reproducibility.


In the fields of science, engineering, industry, and statistics, the accuracy of a measurement system means to what degree measurements of a quantity approximate that quantity’s actual (true) value.

The precision of a measurement system, also called reproducibility or repeatability, is the degree to which repeated measurements, under unchanged conditions, show the same results. Although the two words reproducibility and repeatability can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. A measurement system can be accurate but not precise, precise but not accurate, neither, or both.

For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. Ideally, a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the known value.

The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States.

This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged.

Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements.

With regard to accuracy, the following can be determined:

 The difference between the mean of the measurements and the reference value: the bias. Establishing and correcting for bias is necessary for calibration.

 The combined effect of the process described in the above and precision.

Precision is sometimes stratified into the following:

 Repeatability—the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and

 Reproducibility—the variation arising using the same measurement process among different instruments and operators, and over longer time periods.

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