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In data processing data are often represented by a combination of items (objects organized in rows), and multiple variables (organized in columns). Values of each variable statistically "vary" (or are distributed) across the variable's domain. A domain is a set of all possible values that a variable is allowed to have.
Then a random variate generation algorithm is any program that halts almost surely and exits with a real number x. This x is called a random variate. (Both assumptions are violated in most real computers. Computers necessarily lack the ability to manipulate real numbers, typically using floating point representations instead.
(For a factor A with two levels, scaled so that low = -1 and high = +1, the effect of A has a mean-unbiased estimator that is evaluated by subtracting the average observed response when A is -1 from the average observed response when A = +1 and dividing the result by 2; division by 2 is needed because the -1 level is 2 scaled units away from ...
A set of random variables, any two of which are independent. parameter Any measured quantity of a statistical population that summarizes or describes an aspect of the population, e.g. a mean or a standard deviation; often a quantity to be estimated based on the corresponding quantity calculated by drawing random samples from the population. Can ...
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Scientific terminology is the part of the language that is used by scientists in the context of their professional activities. While studying nature, scientists often encounter or create new material or immaterial objects and concepts and are compelled to name them.
The use of the term n − 1 is called Bessel's correction, and it is also used in sample covariance and the sample standard deviation (the square root of variance). The square root is a concave function and thus introduces negative bias (by Jensen's inequality ), which depends on the distribution, and thus the corrected sample standard ...
The image above depicts a visual comparison between multivariate analysis of variance (MANOVA) and univariate analysis of variance (ANOVA). In MANOVA, researchers are examining the group differences of a singular independent variable across multiple outcome variables, whereas in an ANOVA, researchers are examining the group differences of sometimes multiple independent variables on a singular ...