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  2. Shape of a probability distribution - Wikipedia

    en.wikipedia.org/wiki/Shape_of_a_probability...

    The shape of a distribution will fall somewhere in a continuum where a flat distribution might be considered central and where types of departure from this include: mounded (or unimodal), U-shaped, J-shaped, reverse-J shaped and multi-modal. [1] A bimodal distribution would have two high points rather than one. The shape of a distribution is ...

  3. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Probability density function (pdf) or probability density: function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.

  4. P–P plot - Wikipedia

    en.wikipedia.org/wiki/P–P_plot

    The resulting goodness of fit of the 45° line gives a measure of the difference between a sample set and the theoretical distribution. A P–P plot can be used as a graphical adjunct to a tests of the fit of probability distributions, [ 4 ] [ 5 ] with additional lines being included on the plot to indicate either specific acceptance regions or ...

  5. Violin plot - Wikipedia

    en.wikipedia.org/wiki/Violin_plot

    Violin plots are similar to box plots, except that they also show the probability density of the data at different values, usually smoothed by a kernel density estimator.A violin plot will include all the data that is in a box plot: a marker for the median of the data; a box or marker indicating the interquartile range; and possibly all sample points, if the number of samples is not too high.

  6. Empirical distribution function - Wikipedia

    en.wikipedia.org/wiki/Empirical_distribution...

    The empirical distribution function is an estimate of the cumulative distribution function that generated the points in the sample. It converges with probability 1 to that underlying distribution, according to the Glivenko–Cantelli theorem.

  7. Sampling distribution - Wikipedia

    en.wikipedia.org/wiki/Sampling_distribution

    In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic.If an arbitrarily large number of samples, each involving multiple observations (data points), were separately used in order to compute one value of a statistic (such as, for example, the sample mean or sample variance) for each sample, then the sampling ...

  8. Sample space - Wikipedia

    en.wikipedia.org/wiki/Sample_space

    A sample space is usually denoted using set notation, and the possible ordered outcomes, or sample points, [5] are listed as elements in the set. It is common to refer to a sample space by the labels S, Ω, or U (for "universal set"). The elements of a sample space may be numbers, words, letters, or symbols.

  9. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    Probability plots for distributions other than the normal are computed in exactly the same way. The normal quantile function Φ −1 is simply replaced by the quantile function of the desired distribution. In this way, a probability plot can easily be generated for any distribution for which one has the quantile function.