Partial derivatives of the function f(x,y)

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Discussion Overview

The discussion revolves around the concept of partial derivatives of the function \( z = f(x, y) \), specifically focusing on the function \( z = 3x^2 + 2y \). Participants explore the implications of taking partial derivatives with respect to \( x \) while keeping \( y \) constant, and the potential variations in slope at different points in the \( x-y \) plane.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant calculates the partial derivative \( \frac{\partial z}{\partial x} = 6x \) and evaluates it at the point \( (3,2) \), suggesting a slope of \( 12 \) in the positive \( x \)-direction.
  • Another participant corrects the slope at \( (3,2) \) to \( 18 \) based on the value of \( x \) at that point.
  • Some participants discuss the nature of the surface defined by the function, noting that for fixed \( y \), the function represents a set of parallel parabolas, leading to consistent slopes for a given \( x \).
  • There is a discussion about the implications of fixing \( y \) and how it relates to the interpretation of partial derivatives, with one participant emphasizing that the partial derivative can depend on both \( x \) and \( y \) in certain models.
  • A later reply introduces the concept of controlling for variables in regression models, questioning the necessity of including additional variables if they do not change the partial derivative.
  • Terminology around keeping \( y \) fixed versus maintaining a constant level of \( z \) is clarified, with a caution against mixing these concepts.
  • Another participant mentions that if the function is separable into \( g(x) + h(y) \), the partial derivative with respect to one variable will not depend on the other.

Areas of Agreement / Disagreement

Participants express differing views on the implications of partial derivatives, particularly regarding the dependence on \( y \) and the interpretation of slopes at various points. There is no consensus on the nuances of these concepts, and the discussion remains unresolved.

Contextual Notes

Participants highlight the importance of visualizing the surface and the potential confusion arising from terminology related to fixing variables and constant levels. The discussion also touches on the limitations of linear models in capturing the behavior of partial derivatives.

fog37
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TL;DR
Partial derivatives of the function f(x,y)
Hello,
Given a function like ##z= 3x^2 +2y##, the partial derivative of z w.r.t. x is equal to: $$\frac {\partial z}{\partial x} = 6x$$

Let's consider the point ##(3,2)##. If we sat on top of the point ##(3,2)## and looked straight in the positive x-direction, the slope The slope would be ##(6)(2)=12##. In taking the partial derivative, we assume that y is fixed, i.e. kept constant at ##y=2##. However, if we picked a different starting point like ##(3,4)## that has a different ##y## value, the partial derivative would still be equal to $$\frac {\partial z}{\partial x} =12 $$.
But I am envisioning a ##z## curve over the x-y plane that may have a different slope in the x-direction at the point ##(3,4)##. That seems possible. However, $$\frac {\partial z}{\partial x} = 6x$$ does not capture the fact that the local slope in the x-direction may be different at different y locations....Where am I off?

Thanks!
 
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fog37 said:
TL;DR Summary: Partial derivatives of the function f(x,y)

The slope would be (6)(2)=12.
\nabla z(x,y)=(6x,2)
\nabla z(3,2)=(18,2)
\nabla z(3,4)=(18,2)
 
Last edited:
Fix y and z is a parabola. As functions of y you have a set of parallel parabolas, so for a given x the slope is the same for all.
 
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Can I add a couple of points to what has already been said.

fog37 said:
Let's consider the point ##(3,2)##. If we sat on top of the point ##(3,2)## and looked straight in the positive x-direction, the slope The slope would be ##(6)(2)=12##.
No, The x-direction slope is ##6x = 6 \times 3 = 18##, not ##12##.

fog37 said:
In taking the partial derivative, we assume that y is fixed, i.e. kept constant at ##y=2##. However, if we picked a different starting point like ##(3,4)## that has a different ##y## value, the partial derivative would still be equal to $$\frac {\partial z}{\partial x} =12 $$.
You mean would still be equal to ##18##, not ##12##.

fog37 said:
But I am envisioning a ##z## curve over the x-y plane
You mean a curved surface over the xy plane. For any point ##(x,y)## the 'height of the surface over that point is ##z=f(x,y)##.

fog37 said:
However, $$\frac {\partial z}{\partial x} = 6x$$ does not capture the fact that the local slope in the x-direction may be different at different y locations....Where am I off?
For this particular surface, the x-slope doesn't depend on ##y##. It helps to envisage the surface. If you can't imagine it, there are various 3D plotters available, e.g. look at this: https://www.math3d.org/IGJSjfMEG

Edit.
 
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Thank you! The surface visualization app helped a lot.

In general, given ##z=f(x,y)##, the partial derivative w.r.t. ##x## can be constant, depend only on ##x##, or depend on both ##x## and ##y##. The partial derivative is the slope at a particular point when we make an infinitesimal step in the x-direction and no step at all in the y-direction. When we say that ##\frac {\partial z} {\partial x}## assumes that we keep ##y## fixed and at some constant level, it does not necessarily imply that that partial derivative cannot depend on ##y## itself (it does only for linear models).

Example: consider the points ##(2,1)## and ##(3,1)##, and the partial derivative $$\frac {\partial z} {\partial x} = 3x+y$$ The slopes are ##7## and ##10##. The ##slope=7## means that constraining/fixing ##y=1##, the derivative is ##\frac {\partial z} {\partial x} = 3x+1##. Keeping ##y## fixed is the same as controlling for the variable ##y##: this means that we are considering the variable ##y## in our model and exploring the change in ##z## for changes in ##x## while #y# is not changing, kept constant. That is what controlling means: considering the variable and keeping it a some fixed value while the other variables change so we can isolate their contributions to the dependent variable.

In the case of multiple linear regression, we could have a model like $$y=3x_1+2x_2$$. We say that 3 is the main effect of ##x_1## when ##x_2## is kept constant because ##\frac {\partial y} {partial x} = 3##. The surface is a tilted plane and the slopes in the ##x_1##-direction are all the same for a a certain value of ##x_1## value regardless of the value of ##x_2##.

If we don't include ##x_2## in our model, we are not controlling for ##x_2## essentially. The ##\frac {\partial y} {partial x}## remains exactly the same, ##3##, even without controlling though...So what is the actual point of including ##x_2## if it really does not change the partial derivative of ##z## w.r.t. ##x_1##?

Sorry for the wordiness...
 
Last edited:
Sounds like you have the right idea.

fog37 said:
When we say that ##\frac {\partial z} {\partial x}## assumes that we keep ##y## fixed and at some constant level,
Beware of terminology and mixing-up two different things.

Keeping ##y## 'fixed' (at a constant value) is one thing.

But a 'constant level' is usually interpreted (in the present context) as a constant value of ##z##, in the same way that a particular contour on a map indicates a constant height-level.

You can't do both at the same time. So it's confusing to say "we keep ##y## fixed and at some constant level".

On a more general point, for surfaces defined by ##z = f(x,y)## (or using other symbols for the variables) it often helps to visualise the surface and imagine your are on it. Then you can ask what happens to your 'height' (##z##) if you move in a particular direction.
 
If your function is of the form g(x) + h(y), the partial derivative with respect to one variable will never depend on the other; if you want that then you need a more general form.
 

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