Chain rule (multivariable calculus)

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Homework Help Overview

The discussion revolves around the application of the chain rule in multivariable calculus, specifically focusing on evaluating a function defined by its partial derivatives and exploring linear approximations along a parameterized path.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the evaluation of a function's change along a parameter, with some suggesting the use of linear approximations and secant lines between specific points. Others express confusion regarding mathematical notation and formatting.

Discussion Status

There are multiple lines of reasoning being explored, including the use of gradients and tangent planes. Some participants have offered guidance on approximations and the interpretation of paths in the context of the problem, while others are seeking clarification on mathematical expressions.

Contextual Notes

Participants mention issues with mathematical formatting and notation, which may affect understanding. There is also a reference to a metaphorical interpretation of the problem involving planting flowers along a path, indicating a creative approach to the discussion.

Poetria
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Homework Statement
Let ##f(x,y)=x^3+y^2+x*y##
Suppose that a point is moving through the plane. At time t , the point is at ## (x(t), y(t))=(t^2, e^{t-1})##. Use linear approximation to estimate the change in f as t goes from 1 to 1.1 . In other words, approximate
Relevant Equations
Multivariable chain rule
##f_x=3*x^2+y##
##f_y=2*y+x##

##(3*(t^2)^2+e^{t-1})*2*t+(2*e^{t-1}+t^2)*e^{t-1}##
Well, I am not sure how to evaluate it.
I got a wrong result by multiplying by 0.1, i.e.
##((3*(t^2)^2+e^{t-1})*2*t+(2*e^{t-1}+t^2)*e^{t-1})*0.1##

I guess it is trivial but I am lost. :(
 
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We are interested in the change along ##t##. So why don't you write ##f(x,y)=f(x(t),y(t))=f(t)## in the first place? Then we have two points at ##t=1## and ##t=1.1##. The linear approximation is the secant through these points:
$$
y=\underbrace{\dfrac{f(1)-f(1.1)}{1-1.1}}_{=:m}\cdot x + b\;\wedge\;f(1)=m\cdot 1+b
$$
Finally, you can check the quality of this approximation by calculating the tangent at ##t=1##:
$$
y=\left. \dfrac{d}{dt}\right|_{t=1}f(t) \cdot x + c =f'(1)x+c\;\wedge\;f(1)=f'(1)\cdot 1 +c
$$
which is the linear approximation if only one point is given.
 
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Many thanks. But I can't read this:
"The linear approximation is the secant through these points:
You can't use 'macro parameter character #' in math mode ?

A nice quote from Leibniz. :) Émilie du Châtelet (my avatar) was Leibnizian. :)
 
Poetria said:
Many thanks. But I can't read this
You need to give me a second to correct my format. Please reload.

"He who hasn't tasted bitter things hasn't earned sweet things." (G. Leibniz)

"Let us choose for ourselves our path in life, and let us try to strew that path with flowers." (E. du Châtelet)

##t\longmapsto f(t)## is the path, and you should plant the flowers at ##t=1## and ##t=1.1.##
 
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fresh_42 said:
You need to give me a second to correct my format. Please reload.

"He who hasn't tasted bitter things hasn't earned sweet things." (G. Leibniz)

"Let us choose for ourselves our path in life, and let us try to strew that path with flowers." (E. du Châtelet)

##t\longmapsto f(t)## is the path, and you should plant the flowers at ##t=1## and ##t=1.1.##
I got:
-10.3022 + 13.3022*x = y
x=1.1
Approximation of the change:
4.33022-3=1.33022

A beautiful metaphor: ##t\longmapsto f(t)## is the path, and you should plant the flowers at ##t=1## and ##t=1.1.##
 
Perhaps a gradient would be also a good idea:
Gradient ##\vec (0.21, 0.105171)##
A tangent plane: 0.21*x + 0.105171*y-0.32

Slope of the gradient: 0.500814
 
Last edited:
Poetria said:
A beautiful metaphor: ##t\longmapsto f(t)## is the path, and you should plant the flowers at ##t=1## and ##t=1.1.##
Yes, but a little bit too fast posted. The path is actually ##t\longmapsto (x(t),y(t))## and ##f(t)## the function values along the path.
 
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