Interval arithmetic is an algorithm for bounding rounding and measurement errors. Calculations are likely to involve rounding errors leading to approximation. Rounding and truncation are typical examples of quantization processes. The method below calculates the running sums method with reduced rounding errors. This error is either due to rounding or truncation. Python provides a codice 129 function for rounding a float to the nearest integer. Rounding real numbers to integers is an example. Cancellation error is exponential relative to rounding error. Corrections are needed to account for rounding errors. As the indent size decreases the error caused by tip rounding increases. Double rounding can be avoided by choosing an adequate rounding for the intermediate computation. Numerical analysis uses machine epsilon to study the effects of rounding error. Hamilton took 9th place with Button rounding off the top ten. This is one method used when rounding to significant figures due to its simplicity. Their hue and saturation are usually the same except for rounding.