# Gaussian distribution/Related Articles

< Gaussian distribution

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Revision as of 07:31, 16 April 2010 by imported>Daniel Mietchen ({{:Normal distribution/Related Articles}})

## Parent topics

- Mathematics [r]: The study of quantities, structures, their relations, and changes thereof.
^{[e]} - Probability theory [r]: Mathematical theory of randomness.
^{[e]} - Probability distribution [r]: Function of a discrete random variable yielding the probability that the variable will have a given value.
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## Subtopics

- Applied statistics [r]: the practice of collecting and interpreting numerical observations for the purpose of generating information.
^{[e]} - Carl Friedrich Gauss [r]: German mathematician, who was one of the most influential figures in the history of mathematics and mathematical physics (1777 – 1855).
^{[e]} - Confidence interval [r]: the range of a random variable, such as the mean of a sample, that — with a specified probability — contains the true value for the population.
^{[e]} - Error function [r]: A function associated with the cumulative distribution function of the normal distribution.
^{[e]} - Errors and residuals in statistics [r]: Comparison of two related notions of mathematical statistics.
^{[e]} - Fourier transform [r]: Decomposition to the sum or integral of functions.
^{[e]} - Gamma function [r]: A mathematical function that extends the domain of factorials to non-integers.
^{[e]} - Partial derivative [r]: A function of several variables is its derivative with respect to one of those variables while all others are kept constant.
^{[e]} - Pascal's triangle [r]: A convenient tabular presentation for the binomial coefficients.
^{[e]} - Photon [r]: elementary particle with zero rest mass and unit spin associated with the electromagnetic field.
^{[e]} - Poisson distribution [r]: a probability distribution that is typically used to model the number of independent events (occurring at a constant average rate) that fall within a stated interval.
^{[e]} - Random number [r]: A member of a sequence of which the successive values cannot be predicted, produced by measurement of physical phenomena, appropriate algorithms, or a combination of the two
^{[e]} - Random variable [r]: a variable whose value is determined by chance rather than as a result of a known cause.
^{[e]} - Standard deviation [r]: A statistical measure for the fluctuation of a random variable about its mean value (the square root of the
*variance*).^{[e]} - Stochastic convergence [r]: A mathematical concept intended to formalize the idea that a sequence of essentially random or unpredictable events sometimes is expected to settle into a pattern.
^{[e]} - Taylor series [r]: Representation of a function as an infinite sum of terms calculated from the values of its derivatives at a single point.
^{[e]} - Variance [r]: A statistical measure of the variability of a random quantity (defined as the mean squared deviation from the mean value).
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