ERROR

in applied mathematics, the difference between a true value and an estimate, or approximation, of that value. In statistics, a common example is the difference between a population mean and the mean of a sample drawn from that population. In numerical analysis, round-off error is exemplified by the difference between the true value of the irrational number p and the value of rational expressions such as 22/7, 355/113, 3.14, or 3.14159. Truncation error results from ignoring all but a finite number of terms of an infinite series. For example, the exponential function ex may be expressed as the sum of the infinite series 1 + x + x2/2 + x3/6 + ... + xn/n! + ...; stopping the calculation after any finite value of n gives an approximation to the value of ex that will be in error, though this error can be made as small as desired by making n large enough. The relative error is the numerical difference divided by the true value; the percentage error is this ratio expressed as a percent. The term random error is sometimes used to distinguish the effects of inherent imprecision from so-called systematic error, which may originate in faulty assumptions or procedures.