Joint Probability :
The chance that two or more events occur together.
Let (X,Y) be a two dimensional discrete random variables.
Let p(xi, yj) be real number associated with each (xi, yj)
i = 1,2,3,............
Then p is called the joint probability function of (X, Y) if the following conditions are satisfied.
p (xi, yj) ≥ for all i, j = 1,2,3,...........
∞ ∞
Σ Σ p(xi, yj) = 1
i = 1 j = 1
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Joint Discontinuity :
If the left and right hand limits exist, but disagree then the graph jump at x = a.
J :
'j' is the unit vector in vector study.
Jacobian :
In vector calculus Jacobian matrix is of all first order derivatives of a vector or scalar valued function with respect to another vector.
Joint Variation :
Joint variation is the same as direct variation with two or more quantities. That is if a quantity varies jointly as two or more other quantities, the ratio of the first quantity to the product of other quantities is a constant. That is x/yz = k.
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