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  2. Probit - Wikipedia

    en.wikipedia.org/wiki/Probit

    Plot of probit function. In probability theory and statistics, the probit function is the quantile function associated with the standard normal distribution.It has applications in data analysis and machine learning, in particular exploratory statistical graphics and specialized regression modeling of binary response variables.

  3. Help:Displaying a formula - Wikipedia

    en.wikipedia.org/wiki/Help:Displaying_a_formula

    It is generally a good practice to convert it to {} format, but coherency must be respected; that is, such a conversion must be done in a whole article, or at least in a whole section. Moreover, such a conversion must be identified as such in the edit summary, and making other changes in the same edit should be avoided.

  4. Notation in probability and statistics - Wikipedia

    en.wikipedia.org/wiki/Notation_in_probability...

    The probability is sometimes written to distinguish it from other functions and measure P to avoid having to define "P is a probability" and () is short for ({: ()}), where is the event space, is a random variable that is a function of (i.e., it depends upon ), and is some outcome of interest within the domain specified by (say, a particular ...

  5. Probability density function - Wikipedia

    en.wikipedia.org/wiki/Probability_density_function

    In probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the ...

  6. Probability distribution - Wikipedia

    en.wikipedia.org/wiki/Probability_distribution

    Probability density function (pdf) or probability density: function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would equal that sample.

  7. Kernel (statistics) - Wikipedia

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

    The first requirement ensures that the method of kernel density estimation results in a probability density function. The second requirement ensures that the average of the corresponding distribution is equal to that of the sample used. If K is a kernel, then so is the function K* defined by K*(u) = λK(λu), where λ > 0. This can be used to ...

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