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The distribution is said to be left-skewed, left-tailed, or skewed to the left, despite the fact that the curve itself appears to be skewed or leaning to the right; left instead refers to the left tail being drawn out and, often, the mean being skewed to the left of a typical center of the data.
When the smaller values tend to be farther away from the mean than the larger values, one has a skew distribution to the left (i.e. there is negative skewness), one may for example select the square-normal distribution (i.e. the normal distribution applied to the square of the data values), [1] the inverted (mirrored) Gumbel distribution, [1 ...
The Laplace distribution; The Lévy skew alpha-stable distribution or stable distribution is a family of distributions often used to characterize financial data and critical behavior; the Cauchy distribution, Holtsmark distribution, Landau distribution, Lévy distribution and normal distribution are special cases. The Linnik distribution
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 ...
An example of a geometric distribution arises from rolling a six-sided die until a "1" appears. Each roll is independent with a 1 / 6 {\displaystyle 1/6} chance of success. The number of rolls needed follows a geometric distribution with p = 1 / 6 {\displaystyle p=1/6} .
The exponentially modified normal distribution is another 3-parameter distribution that is a generalization of the normal distribution to skewed cases. The skew normal still has a normal-like tail in the direction of the skew, with a shorter tail in the other direction; that is, its density is asymptotically proportional to for some positive .
An example of a skewed distribution is personal wealth: Few people are very rich, but among those some are extremely rich. However, many are rather poor. Comparison of mean, median and mode of two log-normal distributions with different skewness. A well-known class of distributions that can be arbitrarily skewed is given by the log-normal ...
Normal probability plot of a sample from a right-skewed distribution – it has an inverted C shape. 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.