Numerical analysis provides a variety of techniques to represent (store) and compute approximations to mathematical numerical values. Errors arise from a trade-off between efficiency (space and computation time) and precision, which is limited anyway, since (using common floating-point arithmetic) only a finite amount of values can be represented exactly. The discrepancy between the exact mathematical value and the stored/computed value is called the approximation error.