Precision and accuracy are used in statistics to describe data taken from a set of measurements. A data set is said to be precise if the values are close to each other. A measurement is said to be accurate if it is close to the exact, known, or acceptable value.

Given various data sets, it is possible to find which one has a higher precision. This can be done by finding the range of each data set. The lower the range of the data set, the more precise it is.

Data Set	Highest Value	Lowest Value	Range
13.1, 13.4, 13.2, 12.9, 12.8, 13.0	13.4	12.8	13.4-12.8=0.6
13.5, 13.1, 13.8, 12.9, 12.9, 13.2	13.8	12.9	13.8-12.9=0.9
13.0, 13.1, 13.0, 12.9, 13.2, 13.1	13.2	12.9	13.2-12.9=0.3

Accuracy, on the other hand, requires a point of reference. Suppose that a company that makes tea cups wants each cup to have a diameter of 4 inches. Three random batches of five cups are inspected and the mean is compared to 4. The batch whose mean is closest to 4 is said to be most accurate.

Data Set	Mean	|Mean-4|
3.97, 4.01, 3.90, 4.02, 4.08	3.97 + 4.01+ 3.90 + 4.02 + 4.08/5=3.996	0.004
3.98, 4.02, 3.95, 4.03, 4.01	3.98 + 4.02 + 3.95 + 4.03 + 4.01/5=3.998	0.002
3.99, 4.09, 4.01 3.92, 4.07	3.99 + 4.09 + 4.01 + 3.92 + 4.07/5=4.016	0.016