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  2. Round-off error - Wikipedia

    en.wikipedia.org/wiki/Round-off_error

    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]

  3. Rounding - Wikipedia

    en.wikipedia.org/wiki/Rounding

    The problem was caused by the index being recalculated thousands of times daily, and always being truncated (rounded down) to 3 decimal places, in such a way that the rounding errors accumulated. Recalculating the index for the same period using rounding to the nearest thousandth rather than truncation corrected the index value from 524.811 up ...

  4. Overpressure ammunition - Wikipedia

    en.wikipedia.org/wiki/Overpressure_ammunition

    Speer Gold Dot 124gr 9mm+P in SIG P226 magazines. Overpressure ammunition, commonly designated as +P or +P+ (pronounced Plus-P or Plus-P-Plus), is small arms ammunition that has been loaded to produce a higher internal pressure when fired than is standard for ammunition of its caliber (see internal ballistics), but less than the pressures generated by a proof round.

  5. 7 blood pressure mistakes that could be throwing off your ...

    www.aol.com/7-blood-pressure-mistakes-could...

    If the cuff is too large or small, measurements will be abnormal, the cardiologist cautioned. "Most blood pressure monitors use either an arm cuff or a wrist cuff," he said.

  6. Machine epsilon - Wikipedia

    en.wikipedia.org/wiki/Machine_epsilon

    By this definition, ε equals the value of the unit in the last place relative to 1, i.e. () (where b is the base of the floating point system and p is the precision) and the unit roundoff is u = ε / 2, assuming round-to-nearest mode, and u = ε, assuming round-by-chop.

  7. Floating-point arithmetic - Wikipedia

    en.wikipedia.org/wiki/Floating-point_arithmetic

    These formats (especially decimal128) are pervasive in financial transactions because, along with the decimal32 format, they allow correct decimal rounding. Quadruple precision (binary128). This is a binary format that occupies 128 bits (16 bytes) and its significand has a precision of 113 bits (about 34 decimal digits).

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