The size of the absolute error is proportional to the magnitude of the number. For numbers in IEEE FPS format, the absolute error is less than The largest absolute rounding error occurs when the exponent is 127 and is approximately since The relative error is the absolute error divided by the magnitude of the number which is approximated. Floating variables should not be used as loop counters or loop increments. Convergence tests for iterative algorithms are limited by the precision of the floating point computations. Operations performed in different orders may give different results.
Errors accumulate over time.
While the relative error for a single operation in single precision floating point is about , algorithms which iterate many times may experience an accumulation of errors which is much larger.