Accuracy and precision are two measures of observational error:
Accuracy measures how close a given set of observations are to their true value Precision measures how close the observations are to each other.In the language of statistics:
Accuracy is a description of systematic errors, a measure of bias Precision is a description of random errors, a measure of variability.In the context of observations made on a ratio or interval scale, a statistical sample can be said to be accurate if its average is close to the true value of the quantity being measured and precise if its standard deviation is small.
See Terminological disambiguation below for i) other words that refer to the same concepts; and ii) the use of the words 'accuracy' and 'precision' to refer to related but different concepts.