The Chain Rule: Learn It 2

The Generalized Chain Rule

Now that we’ve seen how to extend the chain rule to functions of two variables, a natural question arises: Can we extend the rule to more than two variables? The answer is yes.

generalized chain rule

Let [latex]w=f(x_1,x_2,\ldots,x_m)[/latex] be a differentiable function of [latex]m[/latex] variables, and let each [latex]x_i=x_i(t_1,t_2,\ldots,t_n)[/latex] be a differentiable function of [latex]n[/latex] variables. Then:

[latex]\dfrac{\partial w}{\partial t_j}=\dfrac{\partial w}{\partial x_1}\dfrac{\partial x_1}{\partial t_j}+\dfrac{\partial w}{\partial x_2}\frac{\partial x_2}{\partial t_j}+\cdots+\dfrac{\partial w}{\partial x_m}\frac{\partial x_m}{\partial t_j}[/latex]

for any [latex]j\in{1,2,\ldots,n}[/latex].

In the next example, we calculate the derivative of a function of three independent variables where each variable depends on two other variables.

Calculate [latex]\partial w/\partial u[/latex] and [latex]\partial w/\partial v[/latex] using the following functions:[latex]\hspace{9cm}\begin{align}w&=f(x,y,z)=3x^2-2xy+4z^2 \\x&=x(u,v)=e^u\sin v \\y&=y(u,v)=e^y\cos v \\ z&=z(u,v)=e^u. \end{align}[/latex]

Create a tree diagram for the case when

[latex]\large{w=f(x,y,z),x=x(t,u,v),y=y(t,u,v),z=z(t,u,v)}[/latex]

and write out the formulas for the three partial derivatives of [latex]w[/latex].