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  2. Covariation model - Wikipedia

    en.wikipedia.org/wiki/Covariation_model

    Covariation model. Harold Kelley 's covariation model (1967, 1971, 1972, 1973) [1] is an attribution theory in which people make causal inferences to explain why other people and ourselves behave in a certain way. It is concerned with both social perception and self-perception (Kelley, 1973). The covariation principle states that, "an effect is ...

  3. Covariance - Wikipedia

    en.wikipedia.org/wiki/Covariance

    Covariance. The sign of the covariance of two random variables X and Y. Covariance in probability theory and statistics is a measure of the joint variability of two random variables. [1] The sign of the covariance, therefore, shows the tendency in the linear relationship between the variables. If greater values of one variable mainly correspond ...

  4. Covariance and correlation - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_correlation

    correlation. so that. where E is the expected value operator. Notably, correlation is dimensionless while covariance is in units obtained by multiplying the units of the two variables. If Y always takes on the same values as X, we have the covariance of a variable with itself (i.e. ), which is called the variance and is more commonly denoted as ...

  5. Covariance function - Wikipedia

    en.wikipedia.org/wiki/Covariance_function

    The same C(x, y) is called the autocovariance function in two instances: in time series (to denote exactly the same concept except that x and y refer to locations in time rather than in space), and in multivariate random fields (to refer to the covariance of a variable with itself, as opposed to the cross covariance between two different variables at different locations, Cov(Z(x 1), Y(x 2))).

  6. Analysis of covariance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_covariance

    Analysis of covariance ( ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of one or more categorical independent variables (IV) and across one or more continuous variables. For example, the categorical variable (s) might describe treatment ...

  7. Covariance and contravariance of vectors - Wikipedia

    en.wikipedia.org/wiki/Covariance_and_contra...

    A system of n quantities that transform oppositely to the coordinates is then a covariant vector (or covector). This formulation of contravariance and covariance is often more natural in applications in which there is a coordinate space (a manifold) on which vectors live as tangent vectors or cotangent vectors.

  8. Multivariate analysis of covariance - Wikipedia

    en.wikipedia.org/wiki/Multivariate_analysis_of...

    Multivariate analysis of covariance. Multivariate analysis of covariance ( MANCOVA) is an extension of analysis of covariance ( ANCOVA) methods to cover cases where there is more than one dependent variable and where the control of concomitant continuous independent variables – covariates – is required. The most prominent benefit of the ...

  9. Consensus decision-making - Wikipedia

    en.wikipedia.org/wiki/Consensus_decision-making

    Members of the Shimer College Assembly reaching a consensus through deliberation. Consensus decision-making or consensus process (often abbreviated to consensus) is a group decision-making process in which participants develop and decide on proposals with the goal of achieving broad acceptance, defined by its terms as form of consensus.