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a probability distribution that is typically used to model the number of independent events (occurring

a mathematical expression defining the shape of a symmetrical probability distribution curve - sometimes referred to as "peakiness". It is sometimes adjusted to p

...ns]]. The other main class in basic [[probability theory]] is [[continuous probability distribution|continuous probability distributions]]. ...bers ranging from 0 to 1 and their sum is exactly 1, we have a [[discrete probability distribution]], and each "degree of belief" is called a [[probability]].

{{r|Continuous probability distribution}}

{{r|Discrete probability distribution}}

* In [[probability theory]], the '''characteristic function''' of any [[probability distribution]] on the [[real number|real]] line is given by the following formula, where

A [[probability distribution]] is a mathematical approach to quantifying uncertainty. ...discrete values only (typically the positive integers), while [[continuous probability distribution|continuous distributions]] describe variables that can take on arbitrary v

In this definition, ''P'' is a probability distribution on the real numbers.

taken from a probability distribution — depends on the size ''n'' of the sample

taken from a probability distribution — depends on the size ''n'' of the sample

{{r|Probability distribution}}

*That the probability distribution describing the next outcome may grow increasingly similar to a certain dist ...ence of random experiments becoming better and better modeled by a given [[probability distribution]].

...om variables]]: non-deterministic (single) quantities which have certain [[probability distribution]]s. Random variables corresponding to various times (or points, in the cas ...>. There is an obvious compatibility condition, namely, that this marginal probability distribution be the same as the one derived from the full-blown stochastic process. When

...</math> Thus, the phrase "an integer chosen at random" is meaningless if a probability distribution on the integers is not specified. "The uniform distribution on the integers ...screte distributions converging to the normal shape. However, [[Continuous probability distribution|continuous distributions]] (normal, uniform etc.) of random variables are n

...so on. However, the term is typically used in the context of power-law [[probability distribution]]s such as the [[Gutenberg-Richter law]] for earthquake sizes, or scaling r

...ility distribution|distributions]] are treated on three levels: [[Discrete probability distribution|discrete probabilities]], [[probability density function]]s, and [[measure ...istributions. In general, conditional distributions need not be [[discrete probability distribution|atomic]] or [[Absolutely continuous random variable|absolutely continuous]]

...ssessment of risk is possible only on the basis of an assumption about the probability distribution of the relevant variables, and the assumption made in the risk-management m

...[0,5] (measured in metres) and distributed according to some ''unknown'' [[probability distribution]]<ref>This is the case in [[non-parametric statistics]]. On the other hand,

...ssessment of risk is possible only on the basis of an assumption about the probability distribution of the relevant variables, and the assumption made in the risk-management m

{{Image|Normal probability distribution function.gif|right|350px|Plot of the standard normal probability density fu