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  2. Unimodality - Wikipedia

    en.wikipedia.org/wiki/Unimodality

    The definition of "unimodal" was extended to functions of real numbers as well. A common definition is as follows: a function f(x) is a unimodal function if for some value m, it is monotonically increasing for x ≤ m and monotonically decreasing for x ≥ m. In that case, the maximum value of f(x) is f(m) and there are no other local maxima.

  3. 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 ...

  4. Mode (statistics) - Wikipedia

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

    Such a continuous distribution is called multimodal (as opposed to unimodal). In symmetric unimodal distributions, such as the normal distribution, the mean (if defined), median and mode all coincide. For samples, if it is known that they are drawn from a symmetric unimodal distribution, the sample mean can be used as an estimate of the ...

  5. Skewness - Wikipedia

    en.wikipedia.org/wiki/Skewness

    For a unimodal distribution (a distribution with a single peak), negative skew commonly indicates that the tail is on the left side of the distribution, and positive skew indicates that the tail is on the right. In cases where one tail is long but the other tail is fat, skewness does not obey a simple rule.

  6. Kurtosis - Wikipedia

    en.wikipedia.org/wiki/Kurtosis

    Several well-known, unimodal, and symmetric distributions from different parametric families are compared here. Each has a mean and skewness of zero. The parameters have been chosen to result in a variance equal to 1 in each case. The images on the right show curves for the following seven densities, on a linear scale and logarithmic scale:

  7. Bell-shaped function - Wikipedia

    en.wikipedia.org/wiki/Bell-shaped_function

    These functions are typically continuous or smooth, asymptotically approach zero for large negative/positive x, and have a single, unimodal maximum at small x. Hence, the integral of a bell-shaped function is typically a sigmoid function. Bell shaped functions are also commonly symmetric.

  8. 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.

  9. Normal probability plot - Wikipedia

    en.wikipedia.org/wiki/Normal_probability_plot

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