mean

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mean,

in statistics, a type of averageaverage,
number used to represent or characterize a group of numbers. The most common type of average is the arithmetic mean. See median; mode.
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. The arithmetic mean of a group of numbers is found by dividing their sum by the number of members in the group; e.g., the sum of the seven numbers 4, 5, 6, 9, 13, 14, and 19 is 70 so their mean is 70 divided by 7, or 10. Less often used is the geometric mean (for two quantities, the square root of their product; for n quantities, the nth root of their product).

mean

see MEASURES OF CENTRAL TENDENCY.

mean

[mēn]
(mathematics)
A single number that typifies a set of numbers, such as the arithmetic mean, the geometric mean, or the expected value. Also known as mean value.

mean

Maths
a. the second and third terms of a proportion, as b and c in a/b = c/d
b. another name for average See also geometric mean

MEAN

(MongoDB, Express, AngularJS, Node.js) A set of system software used for developing JavaScript-based Web applications. Node.js is server-side JavaScript, while Express provides an abbreviated framework for it. AngularJS is used for client-side JavaScript, and MongoDB is a highly scalable database that supports full clustering and automatic sharding. See MongoDB, Node.js, LAMP and database partitioning.
References in periodicals archive ?
Where x is the n-dimensional pixel vector being classified, r is a tunable parameter, T distance-threshold parameter, and [[mu].sub.i] is the n-dimensional mean vector for class i The function [G.sub.i] (x) is evaluated for each class, and the pixel is assigned to the class with a maximum value of [G.sub.i] (x).
For the Gaussian density [[theta].sub.k] = {[[mu].sub.k], [[LAMBDA].sub.k]} and the minimum [beta]-divergence estimators [mathematical expression not reproducible] for the mean vector [[mu].sub.k] and the diagonal covariance matrix [[LAMBDA].sub.k], respectively, are obtained iteratively as follows:
The mean vector of A and [B.sub.k] is [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII], so the mean vector of C is
Then the total mean vector of all samples can be estimated by:
In (7), [[mu].sub.n] denotes the mean vector, [[SIGMA].sub.n] represents the covariance matrix and [[pi].sub.n] is the prior probability of the nth component.
Then the mean vector [bar.X] is computed and subtracted from each data row to obtain the matrix [X.sub.0] representing the zero-mean data variation.
A single-mode Gaussian distribution models the characteristics of a speaker by a locus (mean vector) and an elliptic (covariance matrix), and vector quantization by a discrete set of samples [5].
The circular descriptive statistics include the mean vector, concentration, and circular standard deviation (Fisher, 1995), and Rao's Spacing Test (Kovach, 2008 and references therein).
Consider a T-dimensional random vector X = ([X.sub.1], ..., [X.sub.T])' having a normal distribution with mean vector [mu] = ([[mu].sub.1], ..., [[mu].sub.T])' and covariance matrix [SIGMA].
[4, 5] used proper orthogonal decomposition (POD) to formulate decision variables involved in designing the airfoil shape and revealed that any design can be decomposed into the mean vector and the fluctuation vector, which is expressed by the linear sum of normalized eigenvectors and orthogonal base vectors.
Among them, [m.sub.i] represents class mean vector of the sample category i; [[parallel][m.sub.i] - [n.sub.j][parallel].sup.2] shows distance between class mean vectors of the sample Category i and Category j; [r.sub.i] and [r.sub.j], respectively, show the class average radius of the sample category i and the sample category j; [n.sub.i] shows the number of samples of the sample category i; [d.sub.i,j] represents the class mean distance between the sample category i and the sample category j.
(2) Calculate the mean vector [[bar.m].sub.i] of sample set [[omega].sub.i] = 1,2) according to (6).