Multivariable Calculus

Vectors and Dot Products

01Vectors, Components, and Length in Space 02Scaling and Adding Vectors: The Parallelogram Rule 03The Dot Product and the Law of Cosines 04Finding Angles in Space With the Dot Product 05The Perpendicularity Test and the Normal Vector to a Plane Problem set0/10 Problem set 20/10 MIT problem set0/2

Determinants and the Cross Product

01The Component of a Vector Along Any Unit Direction 02The 2x2 Determinant and the Area of a Parallelogram 03The 3x3 Determinant and the Volume of a Box 04The Cross Product and the Right-Hand Rule 05The Triple Product and the Volume of a Parallelepiped Problem set0/10 Problem set 20/10 MIT problem set0/2

Matrices and Inverse Matrices

01Why Swapping a Cross Product Flips Its Sign 02The Equation of a Plane Through Three Points 03Matrix Multiplication: Rows Dotted With Columns 04Matrices as Transformations: Identity and Rotation 05The Inverse Matrix and Solving AX = B 06Computing a 3x3 Inverse: Minors, Cofactors, Adjoint Problem set0/10 Problem set 20/10 MIT problem set0/2

Planes and Square Systems

01Planes From a Point and a Normal Vector 02Reading the Normal Vector Off a Plane Equation 03Three Planes, One Point: Solving a 3x3 System 04Invertibility, det A, and the Homogeneous System 05When det A = 0: Coplanar Normals and a Line of Solutions Problem set0/10 Problem set 20/10

Parametric Lines and Curves

01Parametric Equations of a Line Through Two Points 02Where a Line Meets a Plane, and When It Never Does 03The Cycloid: Choosing a Parameter That Is Not Time 04Deriving the Cycloid's Equations From Three Vectors 05Is the Cycloid's Bottom a Corner? Taylor Expansion Finds a Cusp Problem set0/10 Problem set 20/10 MIT problem set0/2

Velocity and Kepler's Law

01Velocity and Speed on the Cycloid: Why the Point Stops Dead 02Acceleration Is a Vector: Turning at Constant Speed Still Counts 03Arc Length and the Unit Tangent: v = T̂ ds/dt 04Equal Areas in Equal Times: Kepler's Second Law and |r × v|05Kepler's Second Law Means the Force Is Central Problem set0/10 Problem set 20/10 MIT problem set0/1

Functions of Several Variables

01Functions of Two Variables: Graphs as Surfaces, Built from Slices 02Level Curves and Contour Plots: A Surface Drawn as a Flat Map 03Reading Contour Plots: Domes, Bowls, Saddles and Mountain Passes 04Partial Derivatives: Change One Variable, Hold the Other Fixed Problem set0/10 Problem set 20/10 MIT problem set0/2

Optimization and Least Squares

01Approximation Formula: Changes in x and y Add, via the Tangent Plane 02Critical Points: Where Both Partial Derivatives Are Zero 03Minimum, Maximum or Saddle Point? Classifying by Completing the Square 04Least Squares: The Best-Fit Line as a Minimization in a and b 05Solving Least Squares: Best-Fit Lines, Exponentials and Parabolas Problem set0/10 Problem set 20/10 MIT problem set0/3

The Second Derivative Test

01Quadratic Critical Points: The Sign of 4ac − b² Decides 02The Second Derivative Test: Classifying by the Sign of AC − B² 03Global Min and Max of x + y + 1/(xy): Boundary and Infinity Problem set0/10 Problem set 20/10 MIT problem set0/1

Differentials and the Chain Rule

01The Total Differential: Why df Is Not Δf, and Its Three Uses 02The Chain Rule: Why It Holds, a Worked Check, and the Product Rule 03Chain Rule for a Change of Variables: Partials in Polar Coordinates Problem set0/10 Problem set 20/10 MIT problem set0/1

Gradients and Constraints

01The Gradient Vector: Why It Is Perpendicular to Level Sets 02Tangent Plane to a Surface From the Gradient: The Hyperboloid 03Directional Derivatives and the Direction of Steepest Ascent Problem set0/10 Problem set 20/10 MIT problem set0/2

01Lagrange Multipliers: Tangent Level Curves and ∇f = λ∇g 02Solving the Lagrange Equations, and Why the Method Works 03The Least-Area Gold Pyramid: Its Top Sits Over the Incenter Problem set0/10 Problem set 20/10 MIT problem set0/1

01Implicit Partial Derivatives: Differentiate the Constraint 02Which Variable Is Held Constant? Subscript Notation 03A Constrained Rate Three Ways: Differentials vs Chain Rule Problem set0/10 Problem set 20/10 MIT problem set0/3

Multiple Integrals

01The Heat Equation: A First Partial Differential Equation 02Double Integrals: Volume Under a Surface by Slicing 03Iterated Integrals Over a Square and a Quarter Disk 04Exchanging the Order of Integration: Redraw the Region Problem set0/10 Problem set 20/10 MIT problem set0/1

01Double Integrals in Polar Coordinates: Why dA = r dr dθ 02Area, Mass, Averages and Center of Mass by Double Integrals 03Moment of Inertia: Spinning a Disk About Its Center and Its Rim Problem set0/10 Problem set 20/10 MIT problem set0/3

01Change of Variables: How a Substitution Rescales Area 02The Jacobian: Why Every Polar Integral Carries an r 03Change of Variables Start to Finish: x²y with u = x, v = xy Problem set0/10 Problem set 20/10 MIT problem set0/1

Vector Fields and Line Integrals

01Vector Fields: Sketching Constant, Radial and Rotating Fields 02Work as a Line Integral: Computing ∫ F · dr Along a Path 03Evaluating ∫ M dx + N dy: One Parameter Along the Curve 04Line Integrals by Geometry: Work Around a Circle with F · T ds Problem set0/10 Problem set 20/10 MIT problem set0/1

01Work Around a Closed Curve: Integrating Piece by Piece 02The Fundamental Theorem for Line Integrals: ∫ ∇f · dr 03Path Independence and Why the Rotation Field Fails It 04Conservative Fields: Four Equivalent Properties Problem set0/10 Problem set 20/10 MIT problem set0/1

01The Gradient Field Test: My = Nx, and Where It Breaks 02Finding a Potential Function by Line Integrals 03Finding a Potential Function by Partial Antiderivatives 04Curl in the Plane: Measuring How a Field Rotates Problem set0/10 Problem set 20/10 MIT problem set0/2

Finding a Potential Function by Line Integrals

How does reading the fundamental theorem backwards turn a line integral along two straight pieces into the potential itself?

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Your summary note

1. The fundamental theorem read backwards
  Write (x_1, y_1) = \int_C \vec F \cdot d\vec r + f(0,0) $for a path from the origin, valid once the test passes, and state that (0,0)$ is a free constant.
2. The two-piece path
  Record that on the hmBcaxis = 0 $and = 0$ , and on the vertical piece = x_1 $and = 0$ , and which integrand survives on each.
3. The worked example $\langle 4x^2 + 8xy,\ 3y^2 + 4x^2\rangle$
  Evaluate both pieces to reach = \tfrac43 x^3 + y^3 + 4x^2 y + c$, then check by taking the gradient.
4. Other choices of path
  Redo the example with the hmBcaxis first to get the same potential, and note when the radial path is the better choice.
Attempt 1 of 2