Is my Multivariable Chain Rule Derivation Correct?

In summary, the conversation discusses the correct method for finding partial derivatives of a function with multiple variables. The chain rule is used when differentiating once, while a tree diagram can be helpful when differentiating multiple times. The conversation also addresses the importance of considering the dependence of one variable on another when computing derivatives.
  • #1
Icebreaker
Please let me know if I derived this correctly (I did it a while back, and can't find the notebook):

[tex]v(x,y)=u(r(x,y),s(x,y))[/tex]

(derivations)

At some point I come across this:

[tex]\frac{\partial}{\partial x} \frac{\partial u}{\partial r}[/tex]

which I wrote as

[tex]\frac{\partial^2 u}{\partial r^2} \frac{\partial r}{\partial x}[/tex]

Is it right?
 
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  • #2
Since u depends on r and s, and r and s are both functions of x, you are going to have to take into account the dependence of x on s.

For any function φ(x,y), [tex]\frac{\partial \phi}{\partial x}= \frac{\partial \phi}{\partial r}}\frac{\partial r}{\partial x}}+ \frac{\partial \phi}{\partial s}}\frac{\partial s}{\partial x}}[/tex].

Now put [tex]\frac{\partial u}{\partial r}}[/tex] in place of φ
You get [tex]\frac{\partial^2 \phi}{\partial r^2}}\frac{\partial r}{\partial x}}+ \frac{\partial^2 \phi}{\partial r\partial s}}\frac{\partial s}{\partial x}}[/tex].
 
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  • #3
hint

I don't think so since du is not equal to dudu
 
  • #4
If you only need to differentiate once then the following procedure might come in handy. Say for example you have f(x,y,z) where x,y,z are functions of s and t and you needed to the find the partial derivative of f wrts. What you could do is draw a tree diagram.

You standard with f and the top and draw out three branches, one to each of x, y and z. In a similar manner you do the same with each of x, y and z. That is, draw two branches from each of x, y and z to s and t. You should get a pyramid like diagram after you do this. To find [tex]\frac{{\partial f}}{{\partial s}}[/tex] all you would need to do is draw the appropriate path/s. In other words you just go from f along any path where the end point is s. You then 'sum your paths.' The only restriction is that you keep going downward.

In this case, you would get:

[tex]
\frac{{\partial f}}{{\partial s}} = \frac{{\partial f}}{{\partial x}}\frac{{\partial x}}{{\partial s}} + \frac{{\partial f}}{{\partial y}}\frac{{\partial y}}{{\partial s}} + \frac{{\partial f}}{{\partial z}}\frac{{\partial z}}{{\partial s}}
[/tex]

someone please correct me if my answer is incorrect because I didn't write it down on paper. :biggrin:
 
  • #5
The chain rule for the first derivative I can handle. It's when you have the second and third derivatives that I can't follow which function is related to what.
 
  • #6
A second derivative is just the first derivative of what you compute for the first derivative. :-p
 

FAQ: Is my Multivariable Chain Rule Derivation Correct?

What is the Multivariable Chain Rule?

The Multivariable Chain Rule is a mathematical rule used to find the derivative of a function with multiple variables. It allows us to calculate how small changes in one variable affect the overall output of a function with multiple variables.

How is the Multivariable Chain Rule applied?

To apply the Multivariable Chain Rule, you must first identify the inner and outer functions in your equation. Then, you can take the derivative of the outer function and multiply it by the derivative of the inner function. This process can be repeated for each variable in the equation.

What is the purpose of the Multivariable Chain Rule?

The Multivariable Chain Rule is used to simplify the process of finding the derivative of a function with multiple variables. It allows us to break down a complex equation into smaller, more manageable parts, making it easier to calculate the overall derivative.

What are some common applications of the Multivariable Chain Rule?

The Multivariable Chain Rule is commonly used in fields such as physics, engineering, economics, and statistics. It can be applied to calculate rates of change, optimization problems, and sensitivity analysis in these fields.

Are there any limitations to the Multivariable Chain Rule?

One limitation of the Multivariable Chain Rule is that it only applies to functions with multiple variables. It cannot be used for functions with only one variable. Additionally, it can become more complex and time-consuming to apply as the number of variables in the equation increases.

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