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  2. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    2.5 < x < 3.0 ⇒ result is 2.75 (10.11 in binary) x = 3.0 ⇒ result is 3 (11.00 in binary) For correct results, each rounding step must remove at least 2 binary digits, otherwise, wrong results may appear. For example, 3.125 RPSP to 1/4 ⇒ result is 3.25; 3.25 RPSP to 1/2 ⇒ result is 3.5; 3.5 round-half-to-even to 1 ⇒ result is 4 (wrong ...

  3. Significant figures - Wikipedia

    en.wikipedia.org/wiki/Significant_figures

    Likewise 0.0123 can be rewritten as 1.23 × 102. The part of the representation that contains the significant figures (1.30 or 1.23) is known as the significand or mantissa. The digits in the base and exponent (10 3 or 102) are considered exact numbers so for these digits, significant figures are irrelevant.

  4. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    Round-to-nearest: () is set to the nearest floating-point number to . When there is a tie, the floating-point number whose last stored digit is even (also, the last digit, in binary form, is equal to 0) is used.

  5. Order of magnitude - Wikipedia

    en.wikipedia.org/wiki/Order_of_magnitude

    For a number written in scientific notation, this logarithmic rounding scale requires rounding up to the next power of ten when the multiplier is greater than the square root of ten (about 3.162). For example, the nearest order of magnitude for 1.7 × 10 8 is 8, whereas the nearest order of magnitude for 3.7 × 10 8 is 9.

  6. Scientific notation - Wikipedia

    en.wikipedia.org/wiki/Scientific_notation

    In engineering notation, this is written 40 × 10 6 m. In SI writing style, this may be written 40 Mm (40 megametres). An inch is defined as exactly 25.4 mm. Using scientific notation, this value can be uniformly expressed to any desired precision, from the nearest tenth of a millimeter 2.54 × 10 1 mm to the nearest nanometer 2.540 0000 × 10 ...

  7. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    For numbers with a base-2 exponent part of 0, i.e. numbers with an absolute value higher than or equal to 1 but lower than 2, an ULP is exactly 2 −23 or about 10 −7 in single precision, and exactly 2 −53 or about 10 −16 in double precision. The mandated behavior of IEEE-compliant hardware is that the result be within one-half of a ULP.

  8. 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 ...

  9. Repeating decimal - Wikipedia

    en.wikipedia.org/wiki/Repeating_decimal

    For example, in duodecimal, ⁠ 1 / 2 ⁠ = 0.6, ⁠ 1 / 3 ⁠ = 0.4, ⁠ 1 / 4 ⁠ = 0.3 and ⁠ 1 / 6 ⁠ = 0.2 all terminate; ⁠ 1 / 5 ⁠ = 0. 2497 repeats with period length 4, in contrast with the equivalent decimal expansion of 0.2; ⁠ 1 / 7 ⁠ = 0. 186A35 has period 6 in duodecimal, just as it does in decimal. If b is an integer base ...