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Multivariable Calculus
Calculus in more than one dimension: surfaces instead of curves, gradients instead of slopes, volumes instead of areas. Everything here is drawn in 3D — a surface you can rotate is worth a page of symbols.
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x^2 - y^2
Core
Partial derivatives and the gradient
Differentiating in one direction at a time; the gradient as the vector of slopes.
gradient of x^2*y - 3x + y^3
Core
Optimisation in several variables
Critical points, the second-derivative test, and Lagrange multipliers.
gradient of x^2 + y^2 - 2x - 4y
Core
Double and triple integrals
Volume under a surface by iterated integration; changing the order and the coordinates.
integrate x^2 dx from 0 to 1
Core
Vector fields, line integrals and the big theorems
Gradient fields, curl and divergence, Green, Stokes and Gauss.
gradient of x^2 + y^2
Chapters from Boelkins et al., Active Calculus Multivariable
Every section of the book, condensed into a lesson with its own practice problems.
1. Precalculus of Multivariable Functions
Why Multivariable?Three Dimensional SpaceVectorsLines in SpacePlanes in SpaceCommon Graphs in Three DimensionsPolar, Cylindrical, and Spherical Coordinates
2. Vector-Valued Functions of One Variable
Classic Calculus ApproachVector-Valued Functions of One VariableCalculus of Vector-Valued Functions of One VariableArc LengthThe TNB FrameCurvatureSplitting the Acceleration Vector
3. Derivatives of Multivariable Functions
Calculus of Several VariablesLimitsFirst-Order Partial DerivativesSecond-Order Partial DerivativesLinearization: Tangent Planes and DifferentialsThe Multivariable Chain RuleHigher DimensionsOptimizationConstrained Optimization: Lagrange Multipliers
4. Multiple Integrals
Integrating Functions of Several VariablesDouble Riemann Sums and Double Integrals over RectanglesIterated IntegralsApplications of Double IntegralsChange of Variables
5. Vector Calculus
Integrating Multivariable Vector-Valued FunctionsThe Idea of a Line IntegralUsing Parameterizations to Calculate Line IntegralsPath-Independent Vector Fields and the Fundamental Theorem of Calculus for Line IntegralsLine Integrals of Scalar FunctionsThe Divergence of a Vector FieldThe Curl of a Vector FieldParameterizations of Surfaces and Surface AreaFlux IntegralsSurface Integrals of Scalar Valued Functions
Chapters from OpenStax Calculus Volume 3
Every section of the book, condensed into a lesson with its own practice problems.
1. Parametric Equations and Polar Coordinates
Parametric EquationsCalculus of Parametric CurvesPolar CoordinatesArea and Arc Length in Polar CoordinatesConic Sections
2. Vectors in Space
Vectors in the PlaneVectors in Three DimensionsThe Dot ProductThe Cross ProductEquations of Lines and Planes in SpaceQuadric SurfacesCylindrical and Spherical Coordinates
3. Vector-Valued Functions
Vector-Valued Functions and Space CurvesCalculus of Vector-Valued FunctionsArc Length and CurvatureMotion in Space
4. Differentiation of Functions of Several Variables
Limits and ContinuityTangent Planes and Linear ApproximationsThe Chain RuleDirectional Derivatives and the GradientMaxima/Minima ProblemsLagrange Multipliers
5. Multiple Integration
Double Integrals over Rectangular RegionsDouble Integrals over General RegionsDouble Integrals in Polar CoordinatesTriple IntegralsTriple Integrals in Cylindrical and Spherical CoordinatesCalculating Centers of Mass and Moments of InertiaChange of Variables in Multiple Integrals
6. Vector Calculus
Line IntegralsConservative Vector FieldsGreen’s TheoremDivergence and CurlSurface IntegralsStokes’ TheoremThe Divergence Theorem
Symbols used here
Derivative with respect to x, holding the other variables fixed.
Vector of partial derivatives; points uphill.
Antiderivative (indefinite) or signed area from a to b (definite).
Integral over a region of the plane; integral around a closed curve.
A quantity with magnitude and direction; a column of numbers.
Σ u_i v_i; the length of v, √(v·v).
Questions people ask
What is a partial derivative?
The ordinary derivative with respect to one variable while every other variable is frozen — the slope of the surface in one coordinate direction.
What does the gradient point at?
Uphill: the direction of steepest increase, with length equal to that steepest slope. It is perpendicular to the level curves.
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