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For example, 13 0 0 has three significant figures (and hence indicates that the number is precise to the nearest ten). Less often, using a closely related convention, the last significant figure of a number may be underlined; for example, "1 3 00" has two significant figures. A decimal point may be placed after the number; for example "1300."
Under these circumstances, all the significant figures go into expressing b. For example, if the precision is 15 figures, and these two numbers, b and the square root, are the same to 15 figures, the difference will be zero instead of the difference ε. A better accuracy can be obtained from a different approach, outlined below.
A reading of 8,000 m, with trailing zeros and no decimal point, is ambiguous; the trailing zeros may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 10 3 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 10 3 m indicates ...
All of the significant digits remain, but the placeholding zeroes are no longer required. Thus 1 230 400 would become 1.2304 × 10 6 if it had five significant digits. If the number were known to six or seven significant figures, it would be shown as 1.230 40 × 10 6 or 1.230 400 × 10 6. Thus, an additional advantage of scientific notation is ...
This gives from 6 to 9 significant decimal digits precision. If a decimal string with at most 6 significant digits is converted to the IEEE 754 single-precision format, giving a normal number, and then converted back to a decimal string with the same number of digits, the final result should match the original string. If an IEEE 754 single ...
For example, 1300 x 0.5 = 700. There are two significant figures (1 and 3) in the number 1300, and there is one significant figure (5) in the number 0.5. Therefore, the product will have only one significant figure. When 650 is rounded to one significant figure the result is 700. For example, 1300 + 0.5 = 1301.
False precision (also called overprecision, fake precision, misplaced precision, and spurious precision) occurs when numerical data are presented in a manner that implies better precision than is justified; since precision is a limit to accuracy (in the ISO definition of accuracy), this often leads to overconfidence in the accuracy, named precision bias.
This template has two different functions dependent on input. If only one parameter is given the template counts the number of significant figures of the given number within the ranges 10 12 to 10 −12 and −10 −12 to −10 12.