How to prove this approximation?

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stevendaryl said:
Your first post asks
which to me seems to be asking for a proof, not giving a proof.
I can't give that proof here because it is not allowed here.
 
Kumar8434 said:
I can't give that proof here because it is not allowed here.
What?

Did you try the approach I suggested in post 3? It is not too different from the one stevendaryl posted, but it allows larger differences between the numbers.
 
Kumar8434 said:
I can't give that proof here because it is not allowed here.

As @mfb pointed out, your formula and mine are actually IDENTICAL.

I have a formula saying: [itex]log^n(x_2) \approx log^n(x_1) + \frac{(x_2 - x_1)}{x_1} \frac{1}{\Pi_{j=1}^n log^j(x_1)}[/itex]

To get your formula, let [itex]x_1 = log(y_1)[/itex] and let [itex]x_2 = log(y_2)[/itex]. This gives:

[itex]log^n(log(y_2)) \approx log^n(log(y_1)) + \frac{(log(y_2) - log(y_1))}{log(y_1)} \frac{1}{\Pi_{j=1}^n log^j(log(y_1))}[/itex]

Which can be written as:

[itex]log^{n+1}(y_2) \approx log^{n+1}(y_1) + (log(y_2) - log(y_1))\frac{1}{log(y_1) \Pi_{j=1}^n log^{j+1}(y_1)}[/itex]
[itex]= log^{n+1}(y_1) + (log(y_2) - log(y_1))\frac{1}{\Pi_{j=1}^{n+1} log^{j}(y_1)}[/itex]

This is your approximation, rearranged, with the change of variables
[itex]x_2 \Rightarrow y_2[/itex]
[itex]x_1 \Rightarrow x_2[/itex]
[itex]n \Rightarrow n+1[/itex]
 
@stevendaryl: The formula is a good approximation even in a range where the approximations you used are no longer valid. Proving that doesn't work with your approach. Which is correct, but not general enough.
 
mfb said:
@stevendaryl: The formula is a good approximation even in a range where the approximations you used are no longer valid. Proving that doesn't work with your approach. Which is correct, but not general enough.

His formula is the same as mine, after substituting [itex]x_2 \Rightarrow log(x_2)[/itex], [itex]x_1 \Rightarrow log(x_1)[/itex], [itex]n \Rightarrow n+1[/itex]. So if my formula is good as long as [itex]\frac{x_2}{x_1} < K[/itex], then the replacement would extend that range to [itex]\frac{x_2}{x_1} < (x_1)^K[/itex].