Multivariable Calculus: Topics and Learning Objectives, Schemes and Mind Maps of Calculus

The key topics and learning objectives for a multivariable calculus course. Topics include multivariable functions, vectors, limits, partial derivatives, directional derivatives, gradient, curl and divergence, optimization, integration, parametrized curves, and vector fields. Students are expected to understand concepts related to 3-d space, equations of planes and spheres, arithmetic on vectors, dot product, cross product, limits, partial derivatives, directional derivatives, gradient, curl and divergence, optimization, integration, parametrized curves, and vector fields.

Typology: Schemes and Mind Maps

2021/2022

Uploaded on 08/05/2022

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Multivariable Calculus Common Topics List1
1. Multivariable Functions
2. 3-D space
(a) Distance
(b) Equations of planes, spheres, etc.
(c) Two-variable function graphs
(d) Sections, level curves, and contour diagrams
3. Vectors
(a) Arithmetic on vectors, graphically and by components
(b) Dot Product and projection
(c) Cross Product
4. Limits are more complicated than in the one-variable case
5. Partial Derivatives
(a) Compute using the definition of partial derivatives
(b) Compute using differentiation rules
(c) Approximate given a contour diagram or other info about a function
(d) Estimate signs from real-world desciption
(e) Find the tangent plane
(f) Compute higher-order partials
(g) Mixed partials are equal under certain conditions
6. Directional derivatives
(a) Estimate from contour diagram
(b) Compute using limit definition
(c) Compute using dot product with the gradient
7. Gradient
(a) Compute the gradient
(b) Points in the direction of fastest increase
(c) Length is the directional derivative in that direction
(d) Perpendicular to level set
(e) Draw gradient vector given a contour diagram
1This list was approved by the department on 4/10/19
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Multivariable Calculus Common Topics List^1

  1. Multivariable Functions
  2. 3-D space (a) Distance (b) Equations of planes, spheres, etc. (c) Two-variable function graphs (d) Sections, level curves, and contour diagrams
  3. Vectors (a) Arithmetic on vectors, graphically and by components (b) Dot Product and projection (c) Cross Product
  4. Limits are more complicated than in the one-variable case
  5. Partial Derivatives (a) Compute using the definition of partial derivatives (b) Compute using differentiation rules (c) Approximate given a contour diagram or other info about a function (d) Estimate signs from real-world desciption (e) Find the tangent plane (f) Compute higher-order partials (g) Mixed partials are equal under certain conditions
  6. Directional derivatives (a) Estimate from contour diagram (b) Compute using limit definition (c) Compute using dot product with the gradient
  7. Gradient (a) Compute the gradient (b) Points in the direction of fastest increase (c) Length is the directional derivative in that direction (d) Perpendicular to level set (e) Draw gradient vector given a contour diagram (^1) This list was approved by the department on 4/10/
  1. Curl and Divergence
  2. Chain Rule
  3. Optimization

(a) Locate and classify critical points in a contour diagram (b) Find critical points given a formula (c) Find maxima and minima (d) Second derivative test (e) Extreme value theorem, including understanding of closed and bounded (f) Lagrange multipliers

  1. Integration

(a) Predict the sign of a multiple integral (b) Compute a multiple integral (c) Sketch region of integration (d) Choose or change the order of integration (e) Polar and cylindrical coordinates

  1. Parametrized Curves

(a) Construct parametrizations of lines, circles, and explicitly defined curves (b) Velocity and speed

  1. Vector Fields

(a) Sketch a vector field with a given formula (b) Recognize a conservative (gradient) vector field (c) Find a formula for a potential function of a vector field

  1. Line Integrals

(a) Given a picture of a vector field, predict the sign of a line integral (b) Compute a line integral using explicit parametrization formula (c) Compute arc length of a curve (d) For a gradient field, compute using the fundamental theorem of line integrals (e) For a gradient field, compute using a reparametrization and path independence (f) For a gradient field, the line integral over a loop is zero

  1. Green’s Theorem