Calculus problem with directional vectors

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The discussion focuses on finding the direction vector for the greatest decrease of the function z = x(y^2) at the point (2, -1, 2). The gradient vector is calculated as = < -y^2, -2xy, 1>, yielding < -1, 4, 1> at the specified point. To determine the direction of greatest decrease, the negative of the normalized gradient vector is utilized. The correct answer from the provided options is determined to be (i - 4j)/sqrt(17), which represents the direction of steepest descent.

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At the point (2,-1,2) on the surface z = x(y^2), find the direction vector for the direction of greatest decrease of z.

A) i - 2j
B) i - 4j
C) (i - 4j)/sqrt(17)
D) -i + 4j
E) i + j

Do I need a function f(x,y,z)? If so then f(x,y,z) = z = xy^2.

Then the gradient vector would be <Fx, Fy, Fz>.

This would be give me. < -y^2, -2xy, 1>

At the point (2,-1,2) we get < -1, 4, 1>

But how do i get the direction of the vector of greatest decrease?

From the choices though it seems they only find the gradient vector of z = F(x,y) = xy^2

In which case the gradient vector is < fx, fy>

< y^2 , 2xy> .
At the point (2, -1 ,2) we get < 1, -4>
Again i am not sure how to find the vector of greatest decrease.

It says in my book the direction of minimum increase is - norm( grad f(x,y,z)). But i am not getting any of these answers can some one help?
 
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jgreene2313 said:
At the point (2,-1,2) on the surface z = x(y^2), find the direction vector for the direction of greatest decrease of z.

A) i - 2j
B) i - 4j
C) (i - 4j)/sqrt(17)
D) -i + 4j
E) i + j

Do I need a function f(x,y,z)? If so then f(x,y,z) = z = xy^2.
No, it's z=f(x,y). You're given a function from R2 to R, not R3 to R.
Then the gradient vector would be <Fx, Fy, Fz>.

This would be give me. < -y^2, -2xy, 1>

At the point (2,-1,2) we get < -1, 4, 1>

But how do i get the direction of the vector of greatest decrease?

From the choices though it seems they only find the gradient vector of z = F(x,y) = xy^2

In which case the gradient vector is < fx, fy>

< y^2 , 2xy> .
At the point (2, -1 ,2) we get < 1, -4>.

Again i am not sure how to find the vector of greatest decrease.

It says in my book the direction of minimum increase is - norm( grad f(x,y,z)). But i am not getting any of these answers can someone help?
I doubt your book says that. The norm of the gradient is a number, not a vector; it doesn't have a direction.

How are the gradient and the rate and direction of maximum increase related?
 

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