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With some exceptions regarding erroneous values, infinities, and denormalized numbers, Excel calculates in double-precision floating-point format from the IEEE 754 specification [1] (besides numbers, Excel uses a few other data types [2]). Although Excel allows display of up to 30 decimal places, its precision for any specific number is no more ...
The Indian numbering system is somewhat more complex: It groups the rightmost three digits altogether (until the hundreds place) and thereafter groups by sets of two digits. For example, one trillion (on the short scale; a million millions) would thus be written as 10,00,00,00,00,000 or 10 kharab. [33]
In computing, a roundoff error, [1] also called rounding error, [2] is the difference between the result produced by a given algorithm using exact arithmetic and the result produced by the same algorithm using finite-precision, rounded arithmetic. [3]
4 decimal places: Approximating a fractional decimal number by one with fewer digits 2.1784: 2.18 2 decimal places Approximating a decimal integer by an integer with more trailing zeros 23217: 23200: 3 significant figures Approximating a large decimal integer using scientific notation: 300999999: 3.01 × 10 8: 3 significant figures
Decimals between 1 and 2: fixed interval 2 −23 (1+2 −23 is the next largest float after 1) Decimals between 2 and 4: fixed interval 2 −22; Decimals between 4 and 8: fixed interval 2 −21... Decimals between 2 n and 2 n+1: fixed interval 2 n-23... Decimals between 2 22 =4194304 and 2 23 =8388608: fixed interval 2 −1 =0.5
00000000000 2 =000 16 is used to represent a signed zero (if F = 0) and subnormal numbers (if F ≠ 0); and; 11111111111 2 =7ff 16 is used to represent ∞ (if F = 0) and NaNs (if F ≠ 0), where F is the fractional part of the significand. All bit patterns are valid encoding. Except for the above exceptions, the entire double-precision number ...
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For example, while a fixed-point representation that allocates 8 decimal digits and 2 decimal places can represent the numbers 123456.78, 8765.43, 123.00, and so on, a floating-point representation with 8 decimal digits could also represent 1.2345678, 1234567.8, 0.000012345678, 12345678000000000, and so on.