Question about the definition of df

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In summary: However, my professor told me that this is not always the case, and that the df is still a good approximation to the change in the function, as long as the df is always tangent to the function at the points of interest. In summary, In calculus, the differential is defined as the linear approximation to the change in a function. The differential is given by df = f'(x)dx, where ##f'(x)## is the approximation to the function at the point ##x##. The differential is always tangent to the function at that point, and the differential is always good enough to approximate the change in the function.
  • #1
saminator910
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I guess I have several definitions of [itex]df[/itex] flying at me, and I am having trouble getting a continuous definition. So in basic Calculus, we are taught [itex]df = f'(x)dx[/itex], and it's taught as sort of a linear approximation of the change of f for small values dx, whch makes sense with the definition of the derivative being a linearization of the change in a function.

[itex]df = f(x+h)-f(x)[/itex]

[itex]f(x+h)-f(x)≈f'(x)h[/itex]

That also makes sense with the higher level definition of a differential being a mapping to the tangent space. I have trouble when I consider a Taylor series based derivation for change in f, it seems to be paradoxical.

[itex]\displaystyle{f(x) = f(a)+f'(a)(x-a)+\frac{f''(a)(x-a)^{2}}{2!}+\frac{f'''(a)(x-a)^{3}}{3!}...}[/itex]

sub [itex]\Delta x = x-a[/itex] and [itex]x = a + \Delta x [/itex]

[itex]\displaystyle{f(\Delta x + a) = f(a)+f'(a)\Delta x+\frac{f''(a)(\Delta x)^{2}}{2!}+\frac{f'''(a)(\Delta x)^{3}}{3!}...}[/itex]

rearrange and you can see the confusion...

[itex]\displaystyle{f(\Delta x + a) -f(a) = f'(a)\Delta x+\frac{f''(a)(\Delta x)^{2}}{2!}+\frac{f'''(a)(\Delta x)^{3}}{3!}...}[/itex]

So now I have different definition of df?? Can anyone explain this to me?
 
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  • #2
I think the source of you confusion is that you have assumed that ##\Delta f## and ##df## are interchangeable. They are not. In general, ##df\ne\Delta f##.

In the calculus texts that I've worked with, the differentials ##dx## and ##df## are defined as ##dx=\Delta x## and ##df=f'(x)dx##. And you get that ##df## is a fair approximation of ##\Delta f=f(x+dx)-f(x)## when ##dx## is small. As you've noted, ##df## corresponds specifically to the change in the linear approximation of ##f##; i.e. ##df=\Delta L##, where ##L## is the linear approximation to ##f##. Higher-order Taylor polynomials give different (usually better) approximations for ##f## and, thus, ##\Delta f##. But that doesn't change our definition of ##dx##.

Note that the ##dx## described above is different from the ##dx## used in integral notation. The ##dx## above is a finite, real number. It is not an infinitesimal. Depending on your approach, the ##dx## of integrals is either an infinitesimal or, more likely, a kind of notational artifact.
 
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  • #3
Thanks, I think I'm starting to get the independence of [itex]\Delta f[/itex] and [itex]df[/itex]. So [itex]df = f'(x)dx[/itex], but [itex]\Delta f[/itex] could not necessarily be even "tangent", it could be secant depending on [itex]h[/itex], whereas [itex]df[/itex] is always a tangential approximation, and [itex]df≈f(x+h)-f(x)[/itex] for very small values of [itex]h[/itex].
 
  • #4
I recently had a breakthrough regarding this topic while I was thinking about something that didn't seem to be directly related. I thought about construction of the integral, and I thought about boxes under the curve. So, We get this.

[itex]\displaystyle\sum f(x_{i})\Delta x \Leftrightarrow \int f(x) dx[/itex]

What if, given the sum was taken such that the boxes were always an under approximation, we also used triangles to better approximate the area, so we added those into each term. So the area of the triangle plus the normal rectangle would be

[itex]f(x_{i})\Delta x + \frac{1}{2} \Delta y \Delta x [/itex].

Now, as things become infinitesimal, we get the following.

[itex] f(x)dx + \frac{1}{2} dy dx[/itex]

We sub [itex]dy=f'(x)dx[/itex], and we get the following

[itex]f(x)dx + \frac{1}{2} f'(x) dx^{2}[/itex]

I was very excited to see this, so to me it would seem that there would be higher order terms to better approximate the geometry, as we see in the taylor series I posted previously
 

1. What does "df" stand for?

"df" stands for degrees of freedom. It is a statistical concept that refers to the number of independent pieces of information that are used to estimate a parameter in a statistical model.

2. How is "df" calculated?

The calculation of "df" depends on the specific statistical test or model being used. In general, it is calculated by subtracting the number of parameters being estimated from the total number of observations in the sample.

3. Why is "df" important in statistics?

"df" is important because it is used to determine the critical values for statistical tests and to calculate the probability of obtaining a certain result. It also helps to ensure that the statistical results are reliable and not influenced by excessive or insufficient data.

4. Can "df" be negative?

No, "df" cannot be negative. It is always a positive value, as it represents the number of independent pieces of information used in a statistical model.

5. What is the relationship between "df" and sample size?

The relationship between "df" and sample size is that as the sample size increases, the "df" also increases. This is because a larger sample size provides more independent pieces of information, allowing for a more accurate estimation of parameters in a statistical model.

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