How Does Rigor Balance with Intuition in the Summation of Exponential Series?

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SUMMARY

The discussion focuses on the balance between rigorous mathematical derivations and intuitive approaches in the context of summing exponential series, specifically referencing the Taylor series representation of the exponential function. The author cites Dunham's non-rigorous argument and contrasts it with Rudin's thorough treatment, particularly in the context of limits involving binomial coefficients and factorials. The conclusion emphasizes that both approaches can converge to the same limit, demonstrating that intuitive simplifications can be valid under certain conditions.

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When I was first introduced to a derivation of the taylor series representation of the exponential function here (pg 25): http://paginas.fisica.uson.mx/horacio.munguia/Personal/Documentos/Libros/Euler The_Master of Us.pdf
I noted the author, Dunham mentioning that the argument was non rigorous. I suspected since that it had to do something with the step involving simplifying the expressions like $\frac{k(k-1)(k-2)}{k^3}$ to $1$ for infinitely large $k$. Later Baby Rudin clarified with the section on $e$ in chapter 3. However I am still faced with some urge to simply argue when faced with sums like $\sum\limits_{n=0}^M {n \choose k}(\frac{x}{n})^{k}$ that terms like $\frac{n(n-1)(n-2)}{n^3}$ go to 1 for sufficiently large n and then just consider the sum $\sum\limits_{k=0}^\infty \frac{x^k}{k!}$. Is there some kind of balance between Rudin's thorough treatment and Euler's intuitive but perhaps loose argument?

The best I could think of is as follows:
Letting $f_n(x)=\sum\limits_{k=0}^n {n \choose k}(\frac{x}{n})^k$
I don't think it is hard to show $|{{f_n(x)}-\sum\limits_{k=0}^n \frac{x^k}{k!}}|<o(1)$
By considering the terms $\frac{n(n-1)}{2}x^2$ like so: $(\frac{1}{2}-\frac{1}{2n})x^2$ and then summing up all the error terms like $-\frac{1}{2n}x^2$.

This leads me to ask about this sum:

$ 1+M(\frac{f}{M})^{\alpha}+\frac{M(M-1)(\frac{f}{M})^{2\alpha}}{2!}+\frac{M(M-1)(M-2)(\frac{f}{M})^{3\alpha}}{3!}+...=\sum\limits_{k=0}^M {M \choose k}(\frac{f}{M})^{k\alpha}$

How would you find the limit of this sum as $M->\infty$?
 
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The limit of this sum can be found using the same approach as before. Letting $g_M(f)=\sum\limits_{k=0}^M {M \choose k}(\frac{f}{M})^{k\alpha}$, we can show that $|{{g_M(f)}-\sum\limits_{k=0}^M \frac{f^{k\alpha}}{k!}}|<o(1)$. By considering the terms $\frac{M(M-1)(M-2)}{3!}f^{3\alpha}$ like so: $(\frac{1}{6}-\frac{1}{6M^2})f^{3\alpha}$ and then summing up all the error terms like $-\frac{1}{6M^2}f^{3\alpha}$. The limit of the sum is therefore $\sum\limits_{k=0}^\infty \frac{f^{k\alpha}}{k!}$.
 

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