Section 4.3 - Partial Derivatives

Section Objectives

  1. Compute the partial derivatives of a function of several variables.
  2. Compute higher-order partial derivatives.
  3. Describe the conditions for equality of higher-order mixed partial derivatives.
  4. Interpret partial derivatives as slopes.



Partial derivatives

Perhaps the simplest way to generalize the Calculus I derivative to functions of several variables is to apply the change independently to each variable. This gives us the partial derivatives:

xf(x,y)=fx(x,y)=limh0f(x+h,y)f(x,y)h

and

yf(x,y)=fy(x,y)=limh0f(x,y+h)f(x,y)h,

provided the limits exist.



It should be clear that each partial derivative treats the other variable as non-changing or constant. There are a few important ideas we can take away from the definitions:

  1. The partial derivatives represent slopes. For example, fx(x,y) is the slope of the surface at the point (x,y) in the direction of the positive x-axis.
  2. Partial derivatives can be evaluated by using our Calculus I derivative rules. We simply treat the other variable as a constant.
  3. Higher-order derivatives are also defined by treating variables as constant.


Examples
















Equality of mixed partials

From the last example, you may expect that mixed partial derivatives must be equal. They don't have to be! But they usually are.


Theorem: Suppose that f(x,y) is defined on an open region R. If fxy and fyx are continuous on R, then fxy=fyx on R.



Examples