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  2. 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:

  3. Empirical probability - Wikipedia

    en.wikipedia.org/wiki/Empirical_probability

    In probability theory and statistics, the empirical probability, relative frequency, or experimental probability of an event is the ratio of the number of outcomes in which a specified event occurs to the total number of trials, [1] i.e. by means not of a theoretical sample space but of an actual experiment.

  4. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Frequency distribution: a table that displays the frequency of various outcomes in a sample. Relative frequency distribution: a frequency distribution where each value has been divided (normalized) by a number of outcomes in a sample (i.e. sample size). Categorical distribution: for discrete random variables with a finite set of values.

  5. Benford's law - Wikipedia

    en.wikipedia.org/wiki/Benford's_law

    The points show the exact formula, P(n) = log 10 (1 + 1/n). The graph tends towards the dashed asymptote passing through (1, log 10 e) with slope −1 in log–log scale. The example in yellow shows that the probability of a number starts with 314 is around 0.00138. The dotted lines show the probabilities for a uniform distribution for comparison.

  6. Coefficient of variation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_variation

    In the examples below, we will take the values given as randomly chosen from a larger population of values.. The data set [100, 100, 100] has constant values. Its standard deviation is 0 and average is 100, giving the coefficient of variation as 0 / 100 = 0

  7. Frequentist probability - Wikipedia

    en.wikipedia.org/wiki/Frequentist_probability

    John Venn, who provided a thorough exposition of frequentist probability in his book, The Logic of Chance [1]. Frequentist probability or frequentism is an interpretation of probability; it defines an event's probability as the limit of its relative frequency in infinitely many trials (the long-run probability). [2]

  8. Marginal distribution - Wikipedia

    en.wikipedia.org/wiki/Marginal_distribution

    For example, suppose P(L = red) = 0.2, P(L = yellow) = 0.1, and P(L = green) = 0.7. Multiplying each column in the conditional distribution by the probability of that column occurring results in the joint probability distribution of H and L, given in the central 2×3 block of entries.

  9. Ogive (statistics) - Wikipedia

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

    The points plotted as part of an ogive are the upper class limit and the corresponding cumulative absolute frequency [2] or cumulative relative frequency. The ogive for the normal distribution (on one side of the mean) resembles (one side of) an Arabesque or ogival arch, which is likely the origin of its name.