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  2. Kolmogorov–Smirnov test - Wikipedia

    en.wikipedia.org/wiki/Kolmogorov–Smirnov_test

    Illustration of the Kolmogorov–Smirnov statistic. The red line is a model CDF, the blue line is an empirical CDF, and the black arrow is the KS statistic.. Kolmogorov–Smirnov test (K–S test or KS test) is a nonparametric test of the equality of continuous (or discontinuous, see Section 2.2), one-dimensional probability distributions that can be used to test whether a sample came from a ...

  3. Kernel (statistics) - Wikipedia

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

    Several types of kernel functions are commonly used: uniform, triangle, Epanechnikov, [2] quartic (biweight), tricube, [3] triweight, Gaussian, quadratic [4] and cosine. In the table below, if K {\displaystyle K} is given with a bounded support , then K ( u ) = 0 {\displaystyle K(u)=0} for values of u lying outside the support.

  4. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Birnbaum–Saunders distribution, also known as the fatigue life distribution, is a probability distribution used extensively in reliability applications to model failure times. The chi distribution. The noncentral chi distribution; The chi-squared distribution, which is the sum of the squares of n independent Gaussian random variables.

  5. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is f ( x ) = 1 2 π σ 2 e − ( x − μ ) 2 2 σ 2 . {\displaystyle f(x)={\frac {1}{\sqrt {2\pi \sigma ^{2}}}}e^{-{\frac ...

  6. Continuous uniform distribution - Wikipedia

    en.wikipedia.org/.../Continuous_uniform_distribution

    If X has a standard uniform distribution, then by the inverse transform sampling method, Y = − λ −1 ln(X) has an exponential distribution with (rate) parameter λ. If X has a standard uniform distribution, then Y = X n has a beta distribution with parameters (1/n,1). As such, The Irwin–Hall distribution is the sum of n i.i.d. U(0,1 ...

  7. Relationships among probability distributions - Wikipedia

    en.wikipedia.org/wiki/Relationships_among...

    The product of independent random variables X and Y may belong to the same family of distribution as X and Y: Bernoulli distribution and log-normal distribution. Example: If X 1 and X 2 are independent log-normal random variables with parameters (μ 1, σ 2 1) and (μ 2, σ 2 2) respectively, then X 1 X 2 is a log-normal random variable with ...

  8. Univariate distribution - Wikipedia

    en.wikipedia.org/wiki/Univariate_distribution

    The univariate continuous uniform distribution on an interval [a, b] has the property that all sub-intervals of the same length are equally likely. Binomial distribution with normal approximation for n = 6 and p = 0.5. Other examples of discrete univariate distributions include the binomial, geometric, negative binomial, and Poisson ...

  9. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    In other words, the terms random sample and IID are synonymous. In statistics, "random sample" is the typical terminology, but in probability, it is more common to say "IID." Identically distributed means that there are no overall trends — the distribution does not fluctuate and all items in the sample are taken from the same probability ...

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