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  2. Radial distribution function - Wikipedia

    en.wikipedia.org/wiki/Radial_distribution_function

    The radial distribution function is usually determined by calculating the distance between all particle pairs and binning them into a histogram. The histogram is then normalized with respect to an ideal gas, where particle histograms are completely uncorrelated. For three dimensions, this normalization is the number density of the system ...

  3. Westgard rules - Wikipedia

    en.wikipedia.org/wiki/Westgard_Rules

    The Westgard rules are a set of statistical patterns, each being unlikely to occur by random variability, thereby raising a suspicion of faulty accuracy or precision of the measurement system. They are used for laboratory quality control, in "runs" consisting of measurements of multiple samples. They are a set of modified Western Electric rules ...

  4. Atomic orbital - Wikipedia

    en.wikipedia.org/wiki/Atomic_orbital

    To see the elongated shape of ψ (x, y, z)2 functions that show probability density more directly, see pictures of d-orbitals below. In quantum mechanics, an atomic orbital (/ ˈɔːrbɪtəl /) is a function describing the location and wave-like behavior of an electron in an atom. [1] This function describes an electron's charge distribution ...

  5. 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 ...

  6. Rule of three (statistics) - Wikipedia

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

    The rule can then be derived [2] either from the Poisson approximation to the binomial distribution, or from the formula (1−p) n for the probability of zero events in the binomial distribution. In the latter case, the edge of the confidence interval is given by Pr( X = 0) = 0.05 and hence (1− p ) n = .05 so n ln (1– p ) = ln .05 ≈ −2.996.

  7. Slater's rules - Wikipedia

    en.wikipedia.org/wiki/Slater's_rules

    An example provided in Slater's original paper is for the iron atom which has nuclear charge 26 and electronic configuration 1s 2 2s 2 2p 6 3s 2 3p 6 3d 6 4s 2.The screening constant, and subsequently the shielded (or effective) nuclear charge for each electron is deduced as: [1]

  8. Normality test - Wikipedia

    en.wikipedia.org/wiki/Normality_test

    Simple back-of-the-envelope test takes the sample maximum and minimum and computes their z-score, or more properly t-statistic (number of sample standard deviations that a sample is above or below the sample mean), and compares it to the 68–95–99.7 rule: if one has a 3σ event (properly, a 3s event) and substantially fewer than 300 samples, or a 4s event and substantially fewer than 15,000 ...

  9. Circular error probable - Wikipedia

    en.wikipedia.org/wiki/Circular_error_probable

    The original concept of CEP was based on a circular bivariate normal distribution (CBN) with CEP as a parameter of the CBN just as μ and σ are parameters of the normal distribution. Munitions with this distribution behavior tend to cluster around the mean impact point, with most reasonably close, progressively fewer and fewer further away ...