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The explicit form of a covariant transformation is best introduced with the transformation properties of the derivative of a function. Consider a scalar function f (like the temperature at a location in a space) defined on a set of points p, identifiable in a given coordinate system , =,, … (such a collection is called a manifold).
Covariant and contravariant components of a vector when the basis is not orthogonal. The general formulation of covariance and contravariance refers to how the components of a coordinate vector transform under a change of basis (passive transformation).
Download as PDF; Printable version; In other projects ... The covariant derivative of a function (scalar) ... Note that this transformation formula is for the mean ...
The relationship between general covariance and general relativity may be summarized by quoting a standard textbook: [3] Mathematics was not sufficiently refined in 1917 to cleave apart the demands for "no prior geometry" and for a geometric, coordinate-independent formulation of physics.
In probability theory and statistics, the covariance function describes how much two random variables change together (their covariance) with varying spatial or temporal separation. For a random field or stochastic process Z ( x ) on a domain D , a covariance function C ( x , y ) gives the covariance of the values of the random field at the two ...
In physics, general covariant transformations are symmetries of gravitation theory on a world manifold. They are gauge transformations whose parameter functions are vector fields on X {\displaystyle X} .
The transformations between frames are all arbitrary (invertible and differentiable) coordinate transformations. The covariant quantities are scalar fields, vector fields, tensor fields etc., defined on spacetime considered as a manifold. Main example of covariant equation is the Einstein field equations.
In statistics, a covariate represents a source of variation that has not been controlled in the experiment and is believed to affect the dependent variable. [8] The aim of such techniques as ANCOVA is to remove the effects of such uncontrolled variation, in order to increase statistical power and to ensure an accurate measurement of the true relationship between independent and dependent ...