Multivariable calculus: Exercises
12 Chain rule
Exercise 1: Practice with matrix multiplication
In this exercise, you’ll get some warm-up practice with matrix multiplication to prepare for the chain rule.
Exercise 2: Practice with the chain rule
Now that you’ve seen how the chain rule works by computing both sides, let’s practice using it directly to compute derivatives of compositions.
Exercise 3: The chain rule and partial derivatives
Recall that when we write the chain rule in terms of partial derivatives, it takes the form \[ \frac{\partial (g\circ f)_i}{\partial x_j}(\mathbf{x}) = \sum_{p=1}^m \frac{\partial g_i}{\partial u_p}(f(\mathbf{x}))\frac{\partial f_p}{\partial x_j}(\mathbf{x}), \] where the \(u_p\) are the variables in the domain of \(g\). Very often, we use a shorthand notation that omits the evaluations and lets the \(u_p\) play a double role as both coordinate functions of \(f\) and variables in the domain of \(g\).
Exercise 4: Application problems
The chain rule is particularly useful for solving related rates problems, where we need to understand how different quantities change with respect to time.