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Multivariable Calculus: Gradient Vectors, Hessian Matrices, & Extrema

Classify multivariable critical points using Hessian matrices. Master saddle points, local minima, and gradient vector fields.

Standardized Exam Prompt / Problem

"Classify the critical points of f(x, y) = x^3 + y^3 - 3xy using the Second Partial Derivative Test (Hessian determinant)."

Free Diagnostic Evaluation & Error Analysis

Step 1: Set grad(f) = (3x^2 - 3y, 3y^2 - 3x) = (0, 0). Find critical points (0, 0) and (1, 1). Compute D = f_xx * f_yy - (f_xy)^2.

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