Arithmetic precision
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The precision of a value describes the number of digits that are used to express that value. In a scientific setting this would be the total number of digits (sometimes called the significant figures or significant digits) or, less commonly, the number of fractional digits or decimal places (the number of digits following the point). This second definition is useful in financial and engineering applications where the number of digits in the fractional part has particular importance.
In both cases, the term precision can be used to describe the position at which an inexact result will be rounded. For example, in floating point arithmetic, a result is rounded to a given or fixed precision, which is the length of the resulting significand. In financial calculations, a number is often rounded to a given number of places (for example, to two places after the decimal separator for many world currencies).
As an illustration, the decimal quantity 12.345 can be expressed with various numbers of significant digits or decimal places. If insufficient precision is available then the number is rounded in some manner to fit the available precision. The following table shows the results for various total precisions and decimal places, with the results rounded to nearest where ties round up or to an even digit (the most common rounding modes).
Note that it is often not appropriate to display a figure with more digits than that which can be measured. For instance, if a device measures to the nearest gram and gives a reading of 12.345 kg, it would create false precision if you were to express this measurement as 12.34500 kg.
| Precision |
Rounded to significant digits |
Rounded to decimal places |
|---|---|---|
| Five | 12.345 | 12.34500 |
| Four | 12.35 | 12.3450 |
| Three | 12.3 | 12.345 |
| Two | 12 | 12.35 |
| One | 1 × 101 | 12.3 |
| Zero | n/a | 12 |
The representation of a positive number x to a precision of p significant digits has a numerical value that is given by the formula
For a negative number, the numerical value is minus that of the absolute value. The number 0, to any precision, can be taken to be 0.
[edit] See also
- Round-off error
- Precision (computer science)
- False precision
- IEEE754 (IEEE floating point standard)
