M408M Learning Module Pages

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Chapter 10: Parametric Equations and Polar Coordinates

Chapter 12: Vectors and the Geometry of Space


Chapter 13: Vector Functions


Chapter 14: Partial Derivatives


Learning module LM 14.1: Functions of 2 or 3 variables:

Learning module LM 14.3: Partial derivatives:

      6 pillars of calculus (revisited)
      Geometry of partial derivatives
      Higher partial derivatives

Learning module LM 14.4: Tangent planes and linear approximations:

Learning module LM 14.5: Differentiability and the chain rule:

Learning module LM 14.6: Gradients and directional derivatives:

Learning module LM 14.7: Local maxima and minima:

Learning module LM 14.8: Absolute maxima and Lagrange multipliers:

Chapter 15: Multiple Integrals



Higher partial derivatives

Higher Partial Derivatives

Since $f_x$ and $f_y$ are functions of $x$ and $y$, we can take derivatives of these functions to get second derivatives. There are four such second derivatives, since each time we can differentiate with respect to $x$ or $y$.

The notation for second partial derivatives are as follows:
  • $\displaystyle (f_x)_x = f_{xx} = f_{11}= \frac{\partial}{\partial x} \left( \frac{\partial f}{\partial x} \right) = \frac{\partial ^2 f}{\partial x^2} = \frac{\partial ^2 z}{\partial x^2}$
  • $\displaystyle (f_x)_y = f_{xy} = f_{12} = \frac{\partial}{\partial y} \left( \frac{\partial f}{\partial x} \right) = \frac{\partial ^2 f}{\partial y \partial x} = \frac{\partial ^2 z}{\partial y \partial x}$
  • $\displaystyle (f_y)_x = f_{yx} = f_{21} = \frac{\partial}{\partial x} \left( \frac{\partial f}{\partial y} \right) = \frac{\partial ^2 f}{\partial x \partial y} = \frac{\partial ^2 z}{\partial x \partial y}$
  • $\displaystyle (f_y)_y = f_{yy} = f_{22} =\frac{\partial}{\partial y} \left( \frac{\partial f}{\partial y} \right) = \frac{\partial ^2 f}{\partial y^2} = \frac{\partial ^2 z}{\partial y^2}$
The notation for higher derivatives is similar. $f_{xxyx}$ is what you get by taking a partial derivative of $f$ with respect to $x$, then again with respect to $x$, then with respect to $y$, and finally with respect to $x$.


The main result about higher derivatives is:
Clairaut's Theorem: If $f_{xy}$ and $f_{yx}$ are both defined and continuous in a region containing the point $(a,b)$, then $f_{xy}(a,b)=f_{yx}(a,b)$.

This is often described briefly as mixed partials are equal.


A consequence of this theorem is that we don't need to keep track of the order in which we take derivatives. We just need to keep track of how many times we differentiate with respect to each variable.

Higher partial derivatives and Clairaut's theorem are explained in the following video.