Finding Gradient Vector of f(x,y,z) = 2*sqrt(xyz) at Point (3,-4,-3)

In summary: I got (2, -1, 5). Yes, you have used the chain rule correctly. The gradient vector at (-5,1,3) is (160,-240,400).
  • #1
kasse
384
1
I want to find the gradient vector of f(x,y,z)=2*sqrt(xyz) at the point ((3,-4,-3).

I find the partials and set in for the x-, y-, and z-values, and find the grad. vector (2, (1,5), 2). The right solution is (2, (-1,5), -2), so I have obviously made a mistake with the sqrt. How do I know whether it's + or -?

And another question: Have I used the chain rule correctly when I have calculated the gradient of f(x,y,z) at (-5,1,3) to be (160,-240,400)?
 
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  • #2
what did you get for your gradient??
 
  • #3
Call your variables [itex]x_{i}, i=1,2,3[/tex]
Then, [itex]f(x_{1},x_{2},x_{3})=2\sqrt{x_{1}x_{2}x_{3}}[/itex]
And the partials are:
[tex]\frac{\partial{f}}{\partial{x}_{i}}=\frac{2x_{j}x_{k}}{f}, i,j,k=1,2,3,j\neq{i}\neq{k},j\neq{k}[/tex]
Mind your signs..
 
  • #4
kasse said:
I want to find the gradient vector of f(x,y,z)=2*sqrt(xyz) at the point ((3,-4,-3).

I find the partials and set in for the x-, y-, and z-values, and find the grad. vector (2, (1,5), 2). The right solution is (2, (-1,5), -2), so I have obviously made a mistake with the sqrt. How do I know whether it's + or -?

And another question: Have I used the chain rule correctly when I have calculated the gradient of f(x,y,z) at (-5,1,3) to be (160,-240,400)?
?? You know whether it is + or - (- is correct here) because that's what you get when you do the arithmetic!

What did you get for the gradient vector of [itex]f(x,y,z)= 2\sqrt{xyz}[/itex]?
 

Related to Finding Gradient Vector of f(x,y,z) = 2*sqrt(xyz) at Point (3,-4,-3)

What is the gradient vector of f(x,y,z) at point (3,-4,-3)?

The gradient vector of f(x,y,z) at point (3,-4,-3) is a vector that points in the direction of steepest increase of the function f(x,y,z) at that point. It is defined as the vector formed by taking the partial derivatives of f with respect to each variable, and evaluating them at the given point.

How do you find the gradient vector of a multivariable function?

To find the gradient vector of a multivariable function, you need to take the partial derivatives of the function with respect to each variable, and then evaluate them at the desired point. The resulting vector will be the gradient vector.

What is the significance of the gradient vector in vector calculus?

The gradient vector is an important concept in vector calculus as it represents the direction of the steepest increase of a function, and its magnitude represents the rate of change of the function in that direction. It is also used to find the direction of maximum change or the direction of steepest descent of a function.

Can the gradient vector be used to find the maximum or minimum value of a function?

Yes, the gradient vector can be used to find the maximum or minimum value of a function. This is because the gradient vector points in the direction of steepest increase of the function, so moving in the opposite direction will lead to the maximum or minimum value of the function.

How do you evaluate the gradient vector of a function at a specific point?

To evaluate the gradient vector of a function at a specific point, you need to take the partial derivatives of the function with respect to each variable, and then plug in the values of the variables at the desired point. The resulting vector will be the gradient vector at that point.

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