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- Tails of probability distributions

- Probability theory
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- Probability distributions
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- Theory of probability distributions
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- Tails of probability distributions

- Statistical models
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- Probability distributions
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- Theory of probability distributions
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- Tails of probability distributions

- Statistical theory
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- Probability distributions
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- Theory of probability distributions
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- Tails of probability distributions

Long-tail traffic

A long-tailed or heavy-tailed probability distribution is one that assigns relatively high probabilities to regions far from the mean or median. A more formal mathematical definition is given below. I

Pareto principle

The Pareto principle states that for many outcomes, roughly 80% of consequences come from 20% of causes (the "vital few"). Other names for this principle are the 80/20 rule, the law of the vital few,

Zipf's law

Zipf's law (/zɪf/, German: [ts͡ɪpf]) is an empirical law formulated using mathematical statistics that refers to the fact that for many types of data studied in the physical and social sciences, the r

1% rule

In Internet culture, the 1% rule is a general rule of thumb pertaining to participation in an internet community, stating that only 1% of the users of a website actively create new content, while the

Heavy-tailed distribution

In probability theory, heavy-tailed distributions are probability distributions whose tails are not exponentially bounded: that is, they have heavier tails than the exponential distribution. In many a

Fisher–Tippett–Gnedenko theorem

In statistics, the Fisher–Tippett–Gnedenko theorem (also the Fisher–Tippett theorem or the extreme value theorem) is a general result in extreme value theory regarding asymptotic distribution of extre

Long tail

In statistics and business, a long tail of some distributions of numbers is the portion of the distribution having many occurrences far from the "head" or central part of the distribution. The distrib

Pickands–Balkema–De Haan theorem

The Pickands–Balkema–De Haan theorem gives the asymptotic tail distribution of a random variable, when its true distribution is unknown. It is often called the second theorem in extreme value theory.

Extreme value theory

Extreme value theory or extreme value analysis (EVA) is a branch of statistics dealing with the extreme deviations from the median of probability distributions. It seeks to assess, from a given ordere

Fat-tailed distribution

A fat-tailed distribution is a probability distribution that exhibits a large skewness or kurtosis, relative to that of either a normal distribution or an exponential distribution. In common usage, th

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