For f(x,y)=x²+3y², find fₓ at (2,1).
Answer and explanation
4
Differentiate with respect to x to obtain 2x, then substitute x=2.
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4
Differentiate with respect to x to obtain 2x, then substitute x=2.
z=5+2(x−1)+4(y−2), equivalently z=2x+4y−5.
Credit the correct base height and both gradient coefficients.
6
The gradient is (2,6). Its dot product with (3/5,4/5) is 6/5+24/5=6.
A saddle point
The function increases along the x-axis and decreases along the y-axis.
31
The Hessian is [[4,3],[3,10]]; its determinant is 40−9=31.
A directional derivative is conventionally the rate per unit distance in that direction. Without normalization, the dot product is scaled by the vector length.
Credit the unit-distance interpretation and the scaling effect.
The gradient collects first partial derivatives and determines directional derivatives through a dot product.
UniversityThe gradient collects first partial derivatives and determines directional derivatives through a dot product.
UniversityDraw or describe the region before changing integration order.
UniversityDraw or describe the region before changing integration order.
UniversityHold the other independent variable fixed while differentiating.
UniversityHold the other independent variable fixed while differentiating.
UniversityNormalize a direction vector before the dot product. Here (3/5,4/5) is already a unit vector.
UniversityNormalize a direction vector before the dot product. Here (3/5,4/5) is already a unit vector.
UniversityA positive determinant alone does not distinguish a local minimum from a maximum; inspect fₓₓ as well.
UniversityA positive determinant alone does not distinguish a local minimum from a maximum; inspect fₓₓ as well.
UniversityThe rectangular region allows two independent single-variable integrations.
UniversityThe rectangular region allows two independent single-variable integrations.
UniversityAn integral change of variables uses the absolute determinant; this question asks for its signed value.
UniversityAn integral change of variables uses the absolute determinant; this question asks for its signed value.
UniversityPractise improper integrals, series, gradients and multiple integrals, with explicit conditions and worked examples.
Develop matrix, vector-space and projection reasoning before using least squares.
Connect initial conditions, linear differential equations and numerical approximation with error and conditioning.
Work with conditional probability, normalization, densities and expectation.
Build epsilon proofs and distinguish pointwise convergence, uniform convergence and compactness.
Study groups, vector-space quotients and proof techniques with carefully scoped definitions.
Study complex analysis, residues, Fourier series, PDE boundary conditions and convexity through focused lessons.
Learn descriptive statistics, probability, sampling and inference with worked reasoning.