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Cohen's kappa measures the agreement between two raters who each classify N items into C mutually exclusive categories. The definition of is =, where p o is the relative observed agreement among raters, and p e is the hypothetical probability of chance agreement, using the observed data to calculate the probabilities of each observer randomly selecting each category.
In statistics, a k-statistic is a minimum-variance unbiased estimator of a cumulant. [1] [2] ... This page was last edited on 11 August 2023, at 06:03 (UTC).
Random variables are usually written in upper case Roman letters, such as or and so on. Random variables, in this context, usually refer to something in words, such as "the height of a subject" for a continuous variable, or "the number of cars in the school car park" for a discrete variable, or "the colour of the next bicycle" for a categorical variable.
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.. In statistics, the Kolmogorov–Smirnov test (also 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.
Except for the most common symbols such as letters, numerals, and basic punctuation, rendering of Unicode mathematical symbols can be inconsistent in size or alignment where fallback fonts do not match, and some readers may not have any font which includes certain uncommon symbols. Spaces within a formula must be directly managed (for example ...
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a symbol for psychology; the wave function in the Schrödinger equation of quantum mechanics; represents: the J/psi mesons in particle physics; the stream function in fluid dynamics; the reciprocal Fibonacci constant; the second Chebyshev function in number theory; the polygamma function in mathematics; the supergolden ratio [8]
Given any random variables X 1, X 2, ..., X n, the order statistics X (1), X (2), ..., X (n) are also random variables, defined by sorting the values (realizations) of X 1, ..., X n in increasing order. When the random variables X 1, X 2, ..., X n form a sample they are independent and identically distributed. This is the case treated below.