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  2. Bit error rate - Wikipedia

    en.wikipedia.org/wiki/Bit_error_rate

    The BER is the likelihood of a bit misinterpretation due to electrical noise ().Considering a bipolar NRZ transmission, we have = + for a "1" and () = + for a "0".Each of () and () has a period of .

  3. Error vector magnitude - Wikipedia

    en.wikipedia.org/wiki/Error_Vector_Magnitude

    EVM is generally expressed in percent by multiplying the ratio by 100. [ 1 ] The ideal signal amplitude reference can either be the maximum ideal signal amplitude of the constellation, or it can be the root mean square (RMS) average amplitude of all possible ideal signal amplitude values in the constellation.

  4. Overshoot (signal) - Wikipedia

    en.wikipedia.org/wiki/Overshoot_(signal)

    In control theory, overshoot refers to an output exceeding its final, steady-state value. [2] For a step input, the percentage overshoot (PO) is the maximum value minus the step value divided by the step value.

  5. 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]

  6. Root mean square - Wikipedia

    en.wikipedia.org/wiki/Root_mean_square

    The RMS value of a set of values (or a continuous-time waveform) is the square root of the arithmetic mean of the squares of the values, or the square of the function that defines the continuous waveform.

  7. Statistical significance - Wikipedia

    en.wikipedia.org/wiki/Statistical_significance

    Statistical significance dates to the 18th century, in the work of John Arbuthnot and Pierre-Simon Laplace, who computed the p-value for the human sex ratio at birth, assuming a null hypothesis of equal probability of male and female births; see p-value § History for details.

  8. Observational error - Wikipedia

    en.wikipedia.org/wiki/Observational_error

    This page was last edited on 2 September 2024, at 09:43 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike License 4.0; additional terms may apply.

  9. 68–95–99.7 rule - Wikipedia

    en.wikipedia.org/wiki/68–95–99.7_rule

    In statistics, the 68–95–99.7 rule, also known as the empirical rule, and sometimes abbreviated 3sr, is a shorthand used to remember the percentage of values that lie within an interval estimate in a normal distribution: approximately 68%, 95%, and 99.7% of the values lie within one, two, and three standard deviations of the mean, respectively.