Quantile function

Statistical function that defines the quantiles of a probability distribution

In probability and statistics, the quantile function of a probability distribution is the inverse of its cumulative distribution function. That is, the quantile function of a distribution D {\displaystyle {\mathcal {D}}} is the function Q {\displaystyle Q} such that Pr [ X ≤ Q ( p ) ] = p {\displaystyle \Pr \left[\mathrm {X} \leq Q(p)\right]=p} for any random variable X ∼ D {\displaystyle \mathrm {X} \sim {\mathcal {D}}} and probability p ∈ ( 0 , 1 ) {\displaystyle p\in (0,1)} .

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Quantile function

Statistical function that defines the quantiles of a probability distribution

In probability and statistics, the quantile function of a probability distribution is the inverse of its cumulative distribution function. That is, the quantile function of a distribution D {\displaystyle {\mathcal {D}}} is the function Q {\displaystyle Q} such that Pr [ X ≤ Q ( p ) ] = p {\displaystyle \Pr \left[\mathrm {X} \leq Q(p)\right]=p} for any random variable X ∼ D {\displaystyle \mathrm {X} \sim {\mathcal {D}}} and probability p ∈ ( 0 , 1 ) {\displaystyle p\in (0,1)} .

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From Wikipedia

In probability and statistics, the quantile function of a probability distribution is the inverse of its cumulative distribution function. That is, the quantile function of a distribution D {\displaystyle {\mathcal {D}}} is the function Q {\displaystyle Q} such that Pr [ X ≤ Q ( p ) ] = p {\displaystyle \Pr \left[\mathrm {X} \leq Q(p)\right]=p} for any random variable X ∼ D {\displaystyle \mathrm {X} \sim {\mathcal {D}}} and probability p ∈ ( 0 , 1 ) {\displaystyle p\in (0,1)} . The quantile function is also called the percentile function (after the percentile), percent-point function, inverse cumulative distribution function or inverse distribution function.

Text: Wikipédia, CC BY-SA 4.0. · Image: Ixfd64 (CC0) ·

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