Steply

Directional derivative of f(x, y) = x^3 + 2y^2 at (1, -1) in the…

Step by step, with the reason for every step · Gradient and directional derivative · Calculus 3

Step by step

The question

Question: find the directional derivative of f(x, y) = x³ + 2y² at (1, −1), in the direction of ⟨5, 12⟩.

f(x, y) = x3 + 2y2

1 The partial derivatives

Term by term.

x³: the power 3 comes down.

The power goes down by 1.

So 3x².

2y² has no x: it is a fixed number, so it gives 0.

∂f∂x = 3x2 + 0

Drop the zeros: ∂f/∂x = 3x².

∂f∂x = 3x2

Term by term.

x³ has no y: it is a fixed number, so it gives 0.

2y²: the power 2 comes down: 2 times 2 is 4.

The power goes down by 1.

So 4y.

∂f∂y = 0 + 4y

Drop the zeros: ∂f/∂y = 4y.

∂f∂y = 4y

2 Find the gradient

The gradient ∇f puts the partial derivatives together as one vector.

∇f = ⟨∂f∂x, ∂f∂y⟩

So ∇f = ⟨3x², 4y⟩.

∇f = ⟨3x2, 4y⟩

At the point, put x = 1 and y = −1 in: ∇f(1, −1) = ⟨3, −4⟩.

∇f(1, −1) = ⟨3, −4⟩

3 Make it a unit vector

The direction ⟨5, 12⟩ has length 13.

A direction must have length 1.

‖v‖ = √5² + 12² = 13

So divide each part by 13: u = ⟨5/13, 12/13⟩.

u = ⟨513, 1213⟩

4 Dot with the gradient

The slope in direction u is the gradient dot u.

Duf = ∇f • u

Multiply the matching parts and add.

Duf = 3 × 513 + (−4) × 1213

Careful!

With ⟨5, 12⟩ itself, the answer would be 13 times too big.

Careful: use the unit vector u

3 times 5/13 is 15/13.

−4 times 12/13 is −48/13.

Duf = 1513 − 4813

Add: the slope is −33/13.

Duf = −3313

5 Check

Let's check: take a tiny step of 0.001 along u.

The change in f/0.001 is about −2.54.

f(1.0004, −0.9991) − f(1, −1)0.001 ≈ −2.536

Our answer −33/13 is −2.538.

Almost the same.

Right!

−33/13 = −2.538

Let's look back.

First: the partial derivatives.

Then: find the gradient.

Then: make it a unit vector.

Then: dot with the gradient.

Last: check.

Answer
Duf = −3313

Your turn

Try this one yourself, then check:

Find the directional derivative of f(x, y) = x3 + 3y2
Show the answer
Duf = −1213

More from Gradient and directional derivative

The whole lesson: Gradient and directional derivative →