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  2. Numeric precision in Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Numeric_precision_in...

    Excel's storage of numbers in binary format also affects its accuracy. [3] To illustrate, the lower figure tabulates the simple addition 1 + x − 1 for several values of x. All the values of x begin at the 15 th decimal, so Excel must take them into account. Before calculating the sum 1 + x, Excel first approximates x as a binary number

  3. Quadruple-precision floating-point format - Wikipedia

    en.wikipedia.org/wiki/Quadruple-precision...

    This gives from 33 to 36 significant decimal digits precision. If a decimal string with at most 33 significant digits is converted to the IEEE 754 quadruple-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.

  4. decimal32 floating-point format - Wikipedia

    en.wikipedia.org/wiki/Decimal32_floating-point...

    decimal32 supports 'normal' values, which can have 7 digit precision from ±1.000 000 × 10 ^ −95 up to ±9.999 999 × 10 ^ +96, plus 'subnormal' values with ramp-down relative precision down to ±1. × 10 ^ −101 (one digit), signed zeros, signed infinities and NaN (Not a Number). The encoding is somewhat complex, see below.

  5. Arbitrary-precision arithmetic - Wikipedia

    en.wikipedia.org/wiki/Arbitrary-precision_arithmetic

    But if exact values for large factorials are desired, then special software is required, as in the pseudocode that follows, which implements the classic algorithm to calculate 1, 1×2, 1×2×3, 1×2×3×4, etc. the successive factorial numbers. constants: Limit = 1000 % Sufficient digits.

  6. Module : Location map/data/Germany Frankfurt am Main

    en.wikipedia.org/wiki/Module:Location_map/data/...

    name = Frankfurt am Main Name used in the default map caption; image = Mk_Frankfurt_Nachbargemeinden.png The default map image, without "Image:" or "File:" top = 50.231 Latitude at top edge of map, in decimal degrees

  7. Unit in the last place - Wikipedia

    en.wikipedia.org/wiki/Unit_in_the_last_place

    In computer science and numerical analysis, unit in the last place or unit of least precision (ulp) is the spacing between two consecutive floating-point numbers, i.e., the value the least significant digit (rightmost digit) represents if it is 1. It is used as a measure of accuracy in numeric calculations. [1]

  8. Quater-imaginary base - Wikipedia

    en.wikipedia.org/wiki/Quater-imaginary_base

    Most numbers have a unique quater-imaginary representation, but just as 1 has the two representations 1 = 0. 9 in decimal notation, so, because of 0. 0001 2i = ⁠ 1 / 15 ⁠, the number1 / 5 ⁠ has the two quater-imaginary representations 0. 0003 2i = 3· ⁠ 1 / 15 ⁠ = ⁠ 1 / 5 ⁠ = 1 + 3· ⁠ –4 / 15 ⁠ = 1. 0300 2i.

  9. Fixed-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Fixed-point_arithmetic

    A fixed-point representation of a fractional number is essentially an integer that is to be implicitly multiplied by a fixed scaling factor. For example, the value 1.23 can be stored in a variable as the integer value 1230 with implicit scaling factor of 1/1000 (meaning that the last 3 decimal digits are implicitly assumed to be a decimal fraction), and the value 1 230 000 can be represented ...

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