Significance arithmetic is a set of rules (sometimes called significant figure rules) for approximating the propagation of error in scientific or statistical calculations. These rules can be used to find the appropriate number of significant figures in the result of a calculation. This is important lest the result of a calculation be written with too many or too few significant figures and implicitly show an uncertainty that is either overconfident or underconfident. Understanding these rules requires a good understanding of the concept of significant and insignificant figures.
The rules are an approximation based on statistical rules for dealing with probability distributions. See the article on propagation of uncertainty for these more advanced and precise rules. Significance arithmetic rules rely on the assumption that the number of significant figures in the operands gives accurate information about the uncertainty of the operands and hence the uncertainty of the result. For an alternative see interval arithmetic.
If, in the above, the numbers are assumed to be measurements (and therefore probably inexact) then "8" above represents an inexact measurement with only one significant digit. Therefore, the result of "8 × 8" is rounded to a result with only one significant digit, i.e., "6 × 101" instead of the unrounded "64" that one might expect. In many cases, the rounded result is less accurate than the non-rounded result; a measurement of "8" has an actual underlying quantity between 7.5 and 8.5. The true square would be in the range between 56.25 and 72.25. So 6 × 101 is the best one can give, as other possible answers give a false sense of accuracy. Further, the 6 × 101 is itself confusing (as it might be considered to imply 60 ±5, which is over-optimistic).
Exact numbers are treated as having an unlimited number of significant figures. Examples of such numbers include integer counts (e.g., the number of oranges in a bag, the divisor used in calculating a mean), legal conversion factors such as monetary conversion rates (e.g., there are 2.20371 Dutch guilders to the Euro), or constants that have a value by definition (e.g., one inch = 25.4 mm). Physical constants such as Avogadro's number have a limited number of significant digits, because these constants are only known to us by measurement.
Because significance arithmetic involves rounding, it is useful to understand a specific rounding rule that it is wise to use when doing scientific calculations: the round-to-even rule (also called banker's rounding). It is especially useful when dealing with large data sets or doing calculations on large data sets.
This rule helps to eliminate the upwards skewing of data when using traditional rounding rules. Whereas traditional rounding always rounds up when the following digit is 5, Banker's sometimes rounds down to eliminate this upwards bias.
See the article on rounding for more information on rounding rules and a detailed explanation of the round-to-even rule.
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