Concept

Differentiation rules

Summary
This is a summary of differentiation rules, that is, rules for computing the derivative of a function in calculus. Unless otherwise stated, all functions are functions of real numbers (R) that return real values; although more generally, the formulae below apply wherever they are well defined — including the case of complex numbers (C). For any value of , where , if is the constant function given by , then . Let and . By the definition of the derivative, This shows that the derivative of any constant function is 0. Linearity of differentiation For any functions and and any real numbers and , the derivative of the function with respect to is: In Leibniz's notation this is written as: Special cases include: The constant factor rule The sum rule The subtraction rule Product rule For the functions f and g, the derivative of the function h(x) = f(x) g(x) with respect to x is In Leibniz's notation this is written Chain rule The derivative of the function is In Leibniz's notation, this is written as: often abridged to Focusing on the notion of maps, and the differential being a map , this is written in a more concise way as: Inverse functions and differentiation If the function f has an inverse function g, meaning that and then In Leibniz notation, this is written as Power rule If , for any real number then When this becomes the special case that if then Combining the power rule with the sum and constant multiple rules permits the computation of the derivative of any polynomial. Reciprocal rule The derivative of for any (nonvanishing) function f is: wherever f is non-zero. In Leibniz's notation, this is written The reciprocal rule can be derived either from the quotient rule, or from the combination of power rule and chain rule. Quotient rule If f and g are functions, then: wherever g is nonzero. This can be derived from the product rule and the reciprocal rule. Power rule The elementary power rule generalizes considerably. The most general power rule is the functional power rule: for any functions f and g, wherever both sides are well defined.
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related publications (27)
Related concepts (7)
Logarithmic derivative
In mathematics, specifically in calculus and complex analysis, the logarithmic derivative of a function f is defined by the formula where is the derivative of f. Intuitively, this is the infinitesimal relative change in f; that is, the infinitesimal absolute change in f, namely scaled by the current value of f. When f is a function f(x) of a real variable x, and takes real, strictly positive values, this is equal to the derivative of ln(f), or the natural logarithm of f.
Quotient rule
In calculus, the quotient rule is a method of finding the derivative of a function that is the ratio of two differentiable functions. Let , where both f and g are differentiable and The quotient rule states that the derivative of h(x) is It is provable in many ways by using other derivative rules. Given , let , then using the quotient rule: The quotient rule can be used to find the derivative of as follows: Reciprocal rule The reciprocal rule is a special case of the quotient rule in which the numerator .
Product rule
In calculus, the product rule (or Leibniz rule or Leibniz product rule) is a formula used to find the derivatives of products of two or more functions. For two functions, it may be stated in Lagrange's notation as or in Leibniz's notation as The rule may be extended or generalized to products of three or more functions, to a rule for higher-order derivatives of a product, and to other contexts. Discovery of this rule is credited to Gottfried Leibniz, who demonstrated it using differentials. (However, J. M.
Show more
Related courses (22)
MATH-101(g): Analysis I
Étudier les concepts fondamentaux d'analyse et le calcul différentiel et intégral des fonctions réelles d'une variable.
MATH-106(en): Analysis II (English)
The course studies fundamental concepts of analysis and the calculus of functions of several variables.
MATH-212: Analyse numérique et optimisation
L'étudiant apprendra à résoudre numériquement divers problèmes mathématiques. Les propriétés théoriques de ces méthodes seront discutées.
Show more