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  2. Histogram - Wikipedia

    en.wikipedia.org/wiki/Histogram

    A histogram is a visual representation of the distribution of quantitative data. To construct a histogram, the first step is to "bin" (or "bucket") the range of values— divide the entire range of values into a series of intervals—and then count how many values fall into each interval.

  3. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The expectile distribution, which nests the Gaussian distribution in the symmetric case. The Fisher–Tippett, extreme value, or log-Weibull distribution; Fisher's z-distribution; The skewed generalized t distribution; The gamma-difference distribution, which is the distribution of the difference of independent gamma random variables.

  4. Shape of a probability distribution - Wikipedia

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

    Considerations of the shape of a distribution arise in statistical data analysis, where simple quantitative descriptive statistics and plotting techniques such as histograms can lead on to the selection of a particular family of distributions for modelling purposes. The normal distribution, often called the "bell curve" Exponential distribution

  5. Probability distribution fitting - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution...

    9 Histogram and density function. 10 See also. ... one may for example select the normal distribution, ... The Cauchy distribution is also symmetric.

  6. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    However, a symmetric unimodal or multimodal distribution always has zero skewness. Example of an asymmetric distribution with zero skewness. This figure serves as a counterexample that zero skewness does not imply symmetric distribution necessarily. (Skewness was calculated by Pearson's moment coefficient of skewness.)

  7. Symmetric probability distribution - Wikipedia

    en.wikipedia.org/wiki/Symmetric_probability...

    If a symmetric distribution is unimodal, the mode coincides with the median and mean. All odd central moments of a symmetric distribution equal zero (if they exist), because in the calculation of such moments the negative terms arising from negative deviations from x 0 {\displaystyle x_{0}} exactly balance the positive terms arising from equal ...

  8. Triangular distribution - Wikipedia

    en.wikipedia.org/wiki/Triangular_distribution

    This distribution for a = 0, b = 1 and c = 0.5—the mode (i.e., the peak) is exactly in the middle of the interval—corresponds to the distribution of the mean of two standard uniform variables, that is, the distribution of X = (X 1 + X 2) / 2, where X 1, X 2 are two independent random variables with standard uniform distribution in [0, 1]. [1]

  9. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

    Histogram of a sample from a normal distribution – it looks fairly symmetric and unimodal This is a sample of size 50 from a right-skewed distribution, plotted as both a histogram, and a normal probability plot.