Significant figures
Significant figures (also known as the significant digits, "precision" or "resolution") of a number in positional notation are digits in the number that are reliable and necessary to indicate the quantity of something. If a number expressing the result of a measurement (e.g., length, pressure, volume, or mass) has more digits than the number of digits allowed by the measurement resolution, then only as many digits as allowed by the measurement resolution are reliable, and so only these can be significant figures. For example, if a length measurement gives 114.8 mm while the smallest interval between marks on  the ruler used in the measurement is 1 mm, then the first three digits (1, 1, and 4, showing 114 mm) are certain and so they are significant figures. Digits which are uncertain but "reliable" are also considered significant figures. In this example, the last digit (8, which adds 0.8 mm) is also considered a significant figure even though there is uncertainty in it. Another example is a volume measurement of 2.98 L with an uncertainty of ± 0.05 L. The actual volume is somewhere between 2.93 L and 3.03 L. Even when some of the digits are not certain , as long as they are reliable, they are considered significant because they indicate the actual volume within the acceptable degree of uncertainty. In this example the actual volume might be 2.94 L or might instead be 3.02 L. And so all three are significant figures. The following digits are not significant figures. Of the significant figures in a number, the most significant is the digit with the highest exponent value (simply the left-most significant figure), and the least significant is the digit with the lowest exponent value (simply the right-most significant figure). For example, in the number "123 , the 1" is the most significant figure as it counts hundreds (10), and "3" is the least significant figure as it counts ones (10). Significance arithmetic is a set of approximate rules for roughly maintaining significance throughout a computation. The more sophisticated scientific rules are known as propagation of uncertainty. Numbers are often rounded to avoid reporting insignificant figures. For example, it would create false precision to express a measurement as 12.34525 kg if the scale was only measured to the nearest gram. In this case, the significant figures are the first 5 digits from the left-most digit (1 , 2, 3, 4, and 5), and the number needs to be rounded to the significant figures so that it will be 12.345 kg as the reliable value. Numbers can also be rounded merely for simplicity rather than to indicate a precision of measurement, for example, in order to make the numbers faster to pronounce in news broadcasts. Radix 10 (base-10, decimal numbers) is assumed in the following. Identifying significant figures. Rules to identify significant figures in a number. Note that identifying the significant figures in a number requires knowing which digits are reliable (e.g., by knowing the measurement or reporting  resolution with which the number is obtained or processed) since only reliable digits can be significant; e.g., 3 and 4 in 0.00234 g are not significant if the measurable smallest weight is 0.001 g. Ways to denote significant figures in an integer with trailing zeros. The significance of trailing zeros in a number not containing a decimal point can be ambiguous. For example, it may not always be clear if the number 1300 is precise to the nearest unit (just happens coincidentally to be an exact multiple of a hundred) or if it is only shown to the nearest hundreds  due to rounding or uncertainty. Many conventions exist to address this issue. However, these are not universally used and would only be effective if the reader is familiar with the convention: As the conventions above are not in general use, the following more widely recognized options are available for indicating the significance of number with trailing zeros: Rounding to significant figures. Rounding to significant figures is a more general-purpose technique than rounding to "n" digits, since it handles numbers of different scales in a uniform way. For example, the population of a city might only be known to the  nearest thousand and be stated as 52,000, while the population of a country might only be known to the nearest million and be stated as 52,000,000. The former might be in error by hundreds, and the latter might be in error by hundreds of thousands, but both have two significant figures (5 and 2). This reflects the fact that the significance of the error is the same in both cases, relative to the size of the quantity being measured. To round a number to "n" significant figures: 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. This is done because greater precision is immaterial, and usually it is not possible to settle a debt of less than the smallest currency unit. In UK personal tax returns, income is rounded down to the nearest pound, whilst tax paid is calculated to the nearest penny. As an illustration, the decimal quantity 12.345 can be expressed with various numbers of significant figures 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 precision at two rounding ways (N/A stands for Not Applicable). Another example for 0.012345. (Remember that the leading zeros are not significant.) The representation of a non-zero number "x" to a precision of "p" significant digits has a numerical value that is given by the formula: which may need to be written with a specific marking as detailed above to specify the number of significant trailing zeros. Writing uncertainty and implied uncertainty. Significant figures in writing uncertainty. It is recommended for a measurement result to include the measurement uncertainty such as  formula_5, where "x" and "σ" are the best estimate and uncertainty in the measurement respectively. "x" can be the average of measured values and "σ" can be the standard deviation or a multiple of the measurement deviation. The rules to write formula_5are: Implied uncertainty. In chemistry (and may also be for other scientific branches), uncertainty may be implied by the last significant figure if it is not explicitly expressed. The implied uncertainty is ± the half of the minimum scale at the last significant figure position. For example, if the volume of water in a bottle is reported as 3.78  L without mentioning uncertainty, then ± 0.005 L measurement uncertainty may be implied. If 2.97 ± 0.07 kg, so the actual weight is somewhere in 2.90 to 3.04 kg, is measured and it is desired to report it with a single number, then 3.0 kg is the best number to report since its implied uncertainty ± 0.05 kg tells the weight range of 2.95 to 3.05 kg that is close to the measurement range. If 2.97 ± 0.09 kg, then 3.0 kg is still the best since, if 3 kg is reported then its implied uncertainty ± 0.5 tells the  range of 2.5 to 3.5 kg that is too wide in comparison with the measurement range. If there is a need to write the implied uncertainty of a number, then it can be written as formula_7with stating it as the implied uncertainty (to prevent readers from recognizing it as the measurement uncertainty), where "x" and "σ" are the number with an extra zero digit (to follow the rules to write uncertainty above) and the implied uncertainty of it respectively. For example, 6 kg with the implied uncertainty ± 0.5 kg can be stated as 6.0 ± 0.5 kg. Arithmetic. As  there are rules to determine the significant figures in directly "measured" quantities, there are also guidelines (not rules) to determine the significant figures in quantities "calculated" from these "measured" quantities. Significant figures in "measured" quantities are most important in the determination of significant figures in "calculated quantities" with them. A mathematical or physical constant (e.g., in the formula for the area of a circle with radius as ) has no effect on the determination of the significant figures in the result of a calculation with it if its known digits are equal to or more than the significant figures in the  measured quantities used in the calculation. An exact number such as in the formula for the kinetic energy of a mass with velocity as has no bearing on the significant figures in the calculated kinetic energy since its number of significant figures is infinite (0.500000...). The guidelines described below are intended to avoid a calculation result more precise than the measured quantities, but it does not ensure the resulted implied uncertainty close enough to the measured uncertainties. This problem can be seen in unit conversion. If the guidelines give the implied uncertainty too far from the measured ones, then it  may be needed to decide significant digits that give comparable uncertainty. Multiplication and division. For quantities created from measured quantities via multiplication and division, the calculated result should have as many significant figures as the "least" number of significant figures among the measured quantities used in the calculation. For example, with "one", "two", and "one" significant figures respectively. (2 here is assumed not an exact number.) For the first example, the first multiplication factor has four significant figures and the second has one significant figure. The factor with the fewest or least significant figures is the second one with only  one, so the final calculated result should also have one significant figure. Exception. For unit conversion, the implied uncertainty of the result can be unsatisfactorily higher than that in the previous unit if this rounding guideline is followed; For example, 8 inch has the implied uncertainty of ± 0.5 inch = ± 1.27 cm. If it is converted to the centimetre scale and the rounding guideline for multiplication and division is followed, then 0.32 cm ≈ 20 cm with the implied uncertainty of ± 5 cm. If this implied uncertainty is considered as too underestimated, then more proper significant digits  in the unit conversion result may be 2.32 cm ≈ 20. cm with the implied uncertainty of ± 0.5 cm. Another exception of applying the above rounding guideline is to multiply a number by an integer, such as 1.234 × 9. If the above guideline is followed, then the result is rounded as 1.234 × 9.000... = 11.16 ≈ 11.11. However, this multiplication is essentially adding 1.234 to itself 9 times such as 1.234 + 1.234 + ... + 1.234 so the rounding guideline for addition and subtraction described below is more proper rounding approach. As a result, the final answer  is 1.234 + 1.234 + ... + 1.234 = 11.10 = 11.106 (one significant digit increase). Addition and subtraction. For quantities created from measured quantities via addition and subtraction, the last significant figure position (e.g., hundreds, tens, ones, tenths, hundredths, and so forth) in the calculated result should be the same as the "leftmost" or largest digit position among the last significant figures of the "measured" quantities in the calculation. For example, with the last significant figures in the "ones" place, "tenths" place, and "ones" place respectively. (2 here is assumed not an exact number.) For the first example, the first  term has its last significant figure in the thousandths place and the second term has its last significant figure in the "ones" place. The leftmost or largest digit position among the last significant figures of these terms is the ones place, so the calculated result should also have its last significant figure in the ones place. The rule to calculate significant figures for multiplication and division are not the same as the rule for addition and subtraction. For multiplication and division, only the total number of significant figures in each of the factors in the calculation matters; the digit position  of the last significant figure in each factor is irrelevant. For addition and subtraction, only the digit position of the last significant figure in each of the terms in the calculation matters; the total number of significant figures in each term is irrelevant. However, greater accuracy will often be obtained if some non-significant digits are maintained in intermediate results which are used in subsequent calculations. Logarithm and antilogarithm. The base-10 logarithm of a normalized number (i.e., "a" × 10 with 1 ≤ "a" < 10 and "b" as an integer), is rounded such that its decimal part (called mantissa ) has as many significant figures as the significant figures in the normalized number. When taking the antilogarithm of a normalized number, the result is rounded to have as many significant figures as the significant figures in the decimal part of the number to be antiloged. Transcendental functions. If a transcendental function formula_8 (e.g., the exponential function, the logarithm, and the trigonometric functions) is differentiable at its domain element "x", then its number of significant figures (denoted as "significant figures of formula_8") is approximately related with the number of significant figures in "x" (denoted as "significant figures of "x"") by the  formula formula_10, where formula_11 is the condition number. See the significance arithmetic article to find its derivation. Round only on the final calculation result. When performing multiple stage calculations, do not round intermediate stage calculation results; keep as many digits as is practical (at least one more digit than the rounding rule allows per stage) until the end of all the calculations to avoid cumulative rounding errors while tracking or recording the significant figures in each intermediate result. Then, round the final result, for example, to the fewest number of significant figures (for multiplication or division) or leftmost last significant  digit position (for addition or subtraction) among the inputs in the final calculation. Estimating an extra digit. When using a ruler, initially use the smallest mark as the first estimated digit. For example, if a ruler's smallest mark is 0.1 cm, and 4.5 cm is read, then it is 4.5 (±0.1 cm) or 4.4 cm to 4.6 cm as to the smallest mark interval. However, in practice a measurement can usually be estimated by eye to closer than the interval between the ruler's smallest mark, e.g. in the above case it might be estimated as between 4.51 cm  and 4.53 cm. It is also possible that the overall length of a ruler may not be accurate to the degree of the smallest mark, and the marks may be imperfectly spaced within each unit. However assuming a normal good quality ruler, it should be possible to estimate tenths between the nearest two marks to achieve an extra decimal place of accuracy. Failing to do this adds the error in reading the ruler to any error in the calibration of the ruler. Estimation in statistic. When estimating the proportion of individuals carrying some particular characteristic in a population, from a  random sample of that population, the number of significant figures should not exceed the maximum precision allowed by that sample size. Relationship to accuracy and precision in measurement. Traditionally, in various technical fields, "accuracy" refers to the closeness of a given measurement to its true value; "precision" refers to the stability of that measurement when repeated many times. Hoping to reflect the way in which the term "accuracy" is actually used in the scientific community, there is a recent standard, ISO 5725, which keeps the same definition of precision but defines the term "trueness" as the closeness of a given  measurement to its true value and uses the term "accuracy" as the combination of trueness and precision. (See the accuracy and precision article for a full discussion.) In either case, the number of significant figures roughly corresponds to "precision", not to accuracy or the newer concept of trueness. In computing. Computer representations of floating-point numbers use a form of rounding to significant figures (while usually not keeping track of how many), in general with binary numbers. The number of correct significant figures is closely related to the notion of relative error (which has the advantage of being a more  accurate measure of precision, and is independent of the radix, also known as the base, of the number system used).