Differentiation is linear

This article is about a differentiation rule, i.e., a rule for differentiating a function expressed in terms of other functions whose derivatives are known.
View other differentiation rules

Statement

In terms of additivity and pulling out scalars

The following are true:

• Differentiation is additive, or derivative of sum is sum of derivatives: If $f$ and $g$ are functions that are both differentiable at $x=x_0$, we have:

$\frac{d}{dx}[f(x)+g(x){]}_{x=x_0}=f^{\prime }(x_0)+g^{\prime }(x_0)$

or equivalently:

$(f+g{)}^{\prime }(x_0)=f^{\prime }(x_0)+g^{\prime }(x_0)$

In point-free notation:

$(f+g{)}^{\prime }=f^{\prime }+g^{\prime }$

• Constants (also called scalars) can be pulled out of differentiations: If $f$ is differentiable at $x=x_0$ and $\lambda$ is a real number, then:

$\frac{d}{dx}[\lambda f(x)]{|}_{x=x_0}=\lambda f^{\prime }(x_0)$

In terms of generalized linearity

Suppose $f_1,f_2,\dots ,f_n$ are functions that are all differentiable at a point $x_0$ and $a_1,a_2,\dots ,a_n$ are real numbers. Then:

$\frac{d}{dx}[a_1{f}_1(x)+a_2{f}_2(x)+\dots +a_n{f}_n(x)]{|}_{x=x_0}=a_1{f_{1^{\prime }}}^{\prime }(x_0)+a_2{f_{2^{\prime }}}^{\prime }(x_0)+\dots +a_n{f_{n^{\prime }}}^{\prime }(x_0)$

Related rules

• Repeated differentiation is linear
• Product rule for differentiation
• Product rule for higher derivatives
• Chain rule for differentiation
• Chain rule for higher derivatives
• Definite integration is linear
• Indefinite integration is linear