$$ \newcommand{\RR}{\mathbb{R}} \newcommand{\QQ}{\mathbb{Q}} \newcommand{\CC}{\mathbb{C}} \newcommand{\NN}{\mathbb{N}} \newcommand{\ZZ}{\mathbb{Z}} \newcommand{\EE}{\mathbb{E}} \newcommand{\HH}{\mathbb{H}} \newcommand{\SO}{\operatorname{SO}} \newcommand{\dist}{\operatorname{dist}} \newcommand{\length}{\operatorname{length}} \newcommand{\uppersum}[1]{{\textstyle\sum^+_{#1}}} \newcommand{\lowersum}[1]{{\textstyle\sum^-_{#1}}} \newcommand{\upperint}[1]{{\textstyle\smallint^+_{#1}}} \newcommand{\lowerint}[1]{{\textstyle\smallint^-_{#1}}} \newcommand{\rsum}[1]{{\textstyle\sum_{#1}}} \newcommand{\partitions}[1]{\mathcal{P}_{#1}} \newcommand{\erf}{\operatorname{erf}} \newcommand{\ihat}{\hat{\imath}} \newcommand{\jhat}{\hat{\jmath}} \newcommand{\khat}{\hat{k}} \newcommand{\pmat}[1]{\begin{pmatrix}#1\end{pmatrix}} \newcommand{\smat}[1]{\left(\begin{smallmatrix}#1\end{smallmatrix}\right)} $$

Study Guide II

Write a study guide for yourself in preparation for Midterm I.
You can write the guide however helps you most, but here are some possible suggestions:

The second midterm will focus mostly on the chapter Multivariate Differentiation, and the beginnings of Multivariate Integration (Only the first section, double integrals). Here’s a short cliffnotes of what we have covered (essentially a table of contents of the notes above.)

Differentiation

Functions

  • Understanding graphs of multivariable functions.
  • Understanding level sets of multivariable functions.

Partial Derivatives

  • Know the definition and conceptual meaning of partial derivatives.
  • Be able to use partial derivatives to tell when a function is increasing / decreasing / concave up /concave down in a coordinate direction.
  • Computing implicit partial derivatives, and using them to find slopes.
  • Be able to compute higher order partial derivatives.
  • Being able to express in words what a partial differential equation says. Understanding qualitative behavior of partial differential equations.

Linearization

  • Find implicit and parametric tangent planes to graphs \(z=f(x,y)\).
  • Find normal vectors to graphs of functions \(z=f(x,y)\).
  • Use differentials to estimate the value of a function near a point where you can compute it.
  • Use differentials for error analysis: quantification of error in measurements.

The Gradient

  • Know the definition of the gradient, how to compute it.
  • Be able to use the gradient to compute directional derivatives.
  • Know the geometry of the gradient: specifically, the meanings of its direction and magnitude.
  • Know the relationship between gradients of a function and its level sets.

Extrema

  • Be able to find the critical points of a function
  • Be able to classify the critical points of a function as maxes mins or saddles.
  • Given information about maxes mins and saddles from such a computation, be able to sketch the level sets of a function.

Optimization

  • Understand how to deal with constraints via substitution.
  • Know the concepts behind the technique of Lagrange multipliers
  • Be able to use the technique of Lagrange multipliers to find the maxima and minima of a function along a constraint.
  • Be able to combine Lagrange multipliers with the first and second derivative test of the previous section to solve constrained optimization problems with inequalities.

Integration

Double Integrals

  • Be able to compute the double integral of a function over a rectangle.
  • Be able to compute an iterated integral with variable bounds.
  • Be able to change the order of integration on a double integral.