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  2. GraphCalc - Wikipedia

    en.wikipedia.org/wiki/GraphCalc

    GraphCalc is an open-source computer program that runs in Microsoft Windows and Linux that provides the functionality of a graphing calculator. GraphCalc includes many of the standard features of graphing calculators, but also includes some higher-end features: High resolution

  3. Desmos - Wikipedia

    en.wikipedia.org/wiki/Desmos

    In it, geometrical shapes can be made, as well as expressions from the normal graphing calculator, with extra features. [8] In September 2023, Desmos released a beta for a 3D calculator, which added features on top of the 2D calculator, including cross products, partial derivatives and double-variable parametric equations.

  4. Singular function - Wikipedia

    en.wikipedia.org/wiki/Singular_function

    If f(x) = 0 for all x ≤ a and f(x) = 1 for all x ≥ b, then the function can be taken to represent a cumulative distribution function for a random variable which is neither a discrete random variable (since the probability is zero for each point) nor an absolutely continuous random variable (since the probability density is zero everywhere ...

  5. Probability theory - Wikipedia

    en.wikipedia.org/wiki/Probability_theory

    Furthermore, it covers distributions that are neither discrete nor continuous nor mixtures of the two. An example of such distributions could be a mix of discrete and continuous distributions—for example, a random variable that is 0 with probability 1/2, and takes a random value from a normal distribution with probability 1/2.

  6. Random variable - Wikipedia

    en.wikipedia.org/wiki/Random_variable

    A mixed random variable is a random variable whose cumulative distribution function is neither discrete nor everywhere-continuous. [10] It can be realized as a mixture of a discrete random variable and a continuous random variable; in which case the CDF will be the weighted average of the CDFs of the component variables. [10]

  7. Mean - Wikipedia

    en.wikipedia.org/wiki/Mean

    In all cases, including those in which the distribution is neither discrete nor continuous, the mean is the Lebesgue integral of the random variable with respect to its probability measure. The mean need not exist or be finite; for some probability distributions the mean is infinite (+∞ or −∞), while for others the mean is undefined.

  8. Rectangular function - Wikipedia

    en.wikipedia.org/wiki/Rectangular_function

    Plot of normalized ⁡ function (i.e. ⁡ ()) with its spectral frequency components.. The unitary Fourier transforms of the rectangular function are [2] ⁡ = ⁡ = ⁡ (), using ordinary frequency f, where is the normalized form [10] of the sinc function and ⁡ = ⁡ (/) / = ⁡ (/), using angular frequency , where is the unnormalized form of the sinc function.

  9. Continuous or discrete variable - Wikipedia

    en.wikipedia.org/wiki/Continuous_or_discrete...

    In mathematics and statistics, a quantitative variable may be continuous or discrete if it is typically obtained by measuring or counting, respectively. [1] If it can take on two particular real values such that it can also take on all real values between them (including values that are arbitrarily or infinitesimally close together), the variable is continuous in that interval. [2]