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  2. Median - Wikipedia

    en.wikipedia.org/wiki/Median

    The median of a power law distribution x −a, with exponent a > 1 is 2 1/(a − 1) x min, where x min is the minimum value for which the power law holds [10] The median of an exponential distribution with rate parameter λ is the natural logarithm of 2 divided by the rate parameter: λ −1 ln 2.

  3. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    The cumulative frequency is the total of the absolute frequencies of all events at or below a certain point in an ordered list of events. [1]: 17–19 The relative frequency (or empirical probability) of an event is the absolute frequency normalized by the total number of events:

  4. Median trick - Wikipedia

    en.wikipedia.org/wiki/Median_trick

    The median trick is a generic approach that increases the chances of a probabilistic algorithm to succeed. [1] Apparently first used in 1986 [ 2 ] by Jerrum et al. [ 3 ] for approximate counting algorithms , the technique was later applied to a broad selection of classification and regression problems.

  5. 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 or 3 σ, 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 ...

  6. Prediction interval - Wikipedia

    en.wikipedia.org/wiki/Prediction_interval

    Given a sample from a normal distribution, whose parameters are unknown, it is possible to give prediction intervals in the frequentist sense, i.e., an interval [a, b] based on statistics of the sample such that on repeated experiments, X n+1 falls in the interval the desired percentage of the time; one may call these "predictive confidence intervals".

  7. Median absolute deviation - Wikipedia

    en.wikipedia.org/wiki/Median_absolute_deviation

    Consider the data (1, 1, 2, 2, 4, 6, 9). It has a median value of 2. The absolute deviations about 2 are (1, 1, 0, 0, 2, 4, 7) which in turn have a median value of 1 (because the sorted absolute deviations are (0, 0, 1, 1, 2, 4, 7)). So the median absolute deviation for this data is 1.

  8. Radio spectrum - Wikipedia

    en.wikipedia.org/wiki/Radio_spectrum

    Band designation Frequency range Explanation of meaning of letters; HF: 0.003 to 0.03 GHz: High frequency [18] VHF: 0.03 to 0.3 GHz: Very high frequency [18] UHF: 0.3 to 1 GHz: Ultra-high frequency [18] L: 1 to 2 GHz: Long wave S: 2 to 4 GHz: Short wave C: 4 to 8 GHz: Compromise between S and X X: 8 to 12 GHz: Used in World War II for fire ...

  9. Pseudomedian - Wikipedia

    en.wikipedia.org/wiki/Pseudomedian

    For a time series of length 2N + 1, the pseudomedian is defined as follows. Construct N + 1 sliding windows each of length N + 1. For each window, compute the minimum and maximum. Across all N + 1 windows, find the maximum minimum and the minimum maximum. The pseudomedian is the average of these two quantities.