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Exercise 380Calculus › Multivariable calculus › Partial derivativesL1Added 2 Nov 2026

Partial derivatives and the gradient

#partial derivatives#gradient#chain rule

Statement

Let f(x,y)=x2y+exyf(x,y) = x^2 y + e^{xy}. Compute the partial derivatives ∂f∂x\frac{\partial f}{\partial x} and ∂f∂y\frac{\partial f}{\partial y}, then the gradient ∇f(1,0)\nabla f(1,0).

Hint

Differentiate with respect to xx treating yy as a constant, and vice versa.

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Solution

Partial derivative in xx.
∂f∂x=2xy+yexy.\frac{\partial f}{\partial x} = 2xy + y e^{xy}.

Partial derivative in yy.
∂f∂y=x2+xexy.\frac{\partial f}{\partial y} = x^2 + x e^{xy}.

Gradient at (1,0)(1,0). With x=1,y=0x=1, y=0:
∂f∂x(1,0)=0+0⋅e0=0,∂f∂y(1,0)=1+1⋅e0=2.\frac{\partial f}{\partial x}(1,0) = 0 + 0 \cdot e^0 = 0, \qquad \frac{\partial f}{\partial y}(1,0) = 1 + 1 \cdot e^0 = 2.
Hence
∇f(1,0)=(0,2).\nabla f(1,0) = (0, 2).

Remark. The gradient points in the direction of steepest increase of ff at the given point.