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  2. Differential of a function - Wikipedia

    en.wikipedia.org/wiki/Differential_of_a_function

    A number of properties of the differential follow in a straightforward manner from the corresponding properties of the derivative, partial derivative, and total derivative. These include: [ 11 ] Linearity : For constants a and b and differentiable functions f and g , d ( a f + b g ) = a d f + b d g . {\displaystyle d(af+bg)=a\,df+b\,dg.}

  3. Derivative - Wikipedia

    en.wikipedia.org/wiki/Derivative

    The derivative of ′ is the second derivative, denoted as ⁠ ″ ⁠, and the derivative of ″ is the third derivative, denoted as ⁠ ‴ ⁠. By continuing this process, if it exists, the ⁠ n {\displaystyle n} ⁠ th derivative is the derivative of the ⁠ ( n − 1 ) {\displaystyle (n-1)} ⁠ th derivative or the derivative of order ...

  4. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    The derivative of the function at a point is the slope of the line tangent to the curve at the point. Slope of the constant function is zero, because the tangent line to the constant function is horizontal and its angle is zero. In other words, the value of the constant function, y, will not change as the value of x increases or decreases.

  5. Notation for differentiation - Wikipedia

    en.wikipedia.org/wiki/Notation_for_differentiation

    It is particularly common when the equation y = f(x) is regarded as a functional relationship between dependent and independent variables y and x. Leibniz's notation makes this relationship explicit by writing the derivative as: [1].

  6. Partial derivative - Wikipedia

    en.wikipedia.org/wiki/Partial_derivative

    The graph and this plane are shown on the right. Below, we see how the function looks on the plane y = 1. By finding the derivative of the equation while assuming that y is a constant, we find that the slope of f at the point (x, y) is: = +. So at (1, 1), by substitution, the slope is 3. Therefore,

  7. Inverse function rule - Wikipedia

    en.wikipedia.org/wiki/Inverse_function_rule

    In calculus, the inverse function rule is a formula that expresses the derivative of the inverse of a bijective and differentiable function f in terms of the derivative of f. More precisely, if the inverse of f {\displaystyle f} is denoted as f − 1 {\displaystyle f^{-1}} , where f − 1 ( y ) = x {\displaystyle f^{-1}(y)=x} if and only if f ...

  8. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    For instance, if f(x, y) = x 2 + y 21, then the circle is the set of all pairs (x, y) such that f(x, y) = 0. This set is called the zero set of f, and is not the same as the graph of f, which is a paraboloid. The implicit function theorem converts relations such as f(x, y) = 0 into functions.

  9. Matrix calculus - Wikipedia

    en.wikipedia.org/wiki/Matrix_calculus

    In vector calculus the derivative of a vector y with respect to a scalar x is known as the tangent vector of the vector y, . Notice here that y : R 1 → R m . Example Simple examples of this include the velocity vector in Euclidean space , which is the tangent vector of the position vector (considered as a function of time).