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Many statistics originally derived for particular parametric families have been recognized as U-statistics for general distributions. In non-parametric statistics, the theory of U-statistics is used to establish for statistical procedures (such as estimators and tests) and estimators relating to the asymptotic normality and to the variance (in finite samples) of such quantities. [3]
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.
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5. In probability and statistics, may specify the probability distribution of a random variable. For example, (,) means that the distribution of the random variable X is standard normal. [2] 6. Notation for proportionality. See also ∝ for a less ambiguous symbol. ≡ 1.
The glyph of the up tack appears as an upside-down tee symbol, and as such is sometimes called eet (the word "tee" in reverse). [citation needed] Tee plays a complementary or dual role in many of these theories. The similar-looking perpendicular symbol ( , \perp in LaTeX, U+27C2 in Unicode) is a binary relation symbol used to represent:
Kendall tau rank correlation coefficient, a measure of rank correlation in statistics; Ramanujan's tau function in number theory; shear stress in continuum mechanics; a type variable in type theories, such as the simply typed lambda calculus; path tortuosity in reservoir engineering; in topology, a given topology
Pages in category "U-statistics" The following 4 pages are in this category, out of 4 total. This list may not reflect recent changes. M. Mann–Whitney U test; S.
Inverted U may refer to: Calmfors–Driffill hypothesis , an economic theory describing the relationship between collective bargaining and employment Kuznets curve , an economic theory describing the relationship between income per capita and wealth inequity