Euler edits

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\uptitler{Fall 2022}
\title{Euler's Number}
\subtitle{
By Oleg Gleizer and Olga Radko. \\
Prepared by Mark on \today
Prepared by Mark on \today. \\
Based on a handout by Oleg Gleizer and Olga Radko
}
@ -31,12 +31,14 @@
\section{Compound Interest}
Let $P$ be the primary capital invested at a constant rate $r$ compounded annually. Let $V(t)$ be the value of the investment in $t$ years.
Let $P$ be an amount of primary capital which is invested at an annual rate $r$. \par
Let $V(t)$ be the value of the investment in $t$ years.
\problem{}
Derive the formula for $V(t)$. \\
Derive the formula for $V(t)$ if the annual rate $r$ is compounded monthly. \\
Derive the formula for $V(t)$ if the annual rate $r$ is compounded $n$ times a year, $n \in \mathbb{N}$. \\
Derive the formula for $V(t)$ if the annual rate $r$ is compounded yearly. \par
Derive the formula for $V(t)$ if the annual rate $r$ is compounded monthly. \par
Derive the formula for $V(t)$ if the annual rate $r$ is compounded $n$ times a year, $n \in \mathbb{N}$. \par
\hint{\say{Compound monthly} means that $\frac{1}{12}$ of $r$ is applied every month.}
\begin{solution}
$V(t) = P(1 + \frac{r}{n})^{nt}$
@ -44,369 +46,33 @@
Next, let's try to understand how we can compound interest continuously.
\vfill
\section{Limits}
\definition{}
Let $[a_1, a_2, a_3, ... ]$, or alternately, $[a_n]^\infty_{n=1}$ (abbreviated $[a_n]$ in this handout) be a sequence of real numbers. \\
Any number $u \in \mathbb{R}$ is called an \textit{upper bound} of $[a_n]$ if $a_n \leq u$ for all $u$. \\
We say a sequence $[a_n]$ with an an upper bound is \textit{bounded from above}.
\definition{}
We say a sequence of real numbers $[a_n]^\infty_{n=1}$ is \textit{monotonically increasing} if $m < n \implies a_m < a_n$.
\vfill
\theorem{}<limexists>
A monotonically increasing sequence that is bounded from above has a unique limit. \\
Intuitively, the limit of a sequence is a point to which the sequence gets closer and closer to. Consider the following examples: $[\frac{1}{1}, \frac{1}{2}, \frac{1}{4}, \frac{1}{4}, ...]$, which has the limit $0$, and the sequence $[3, 3.1, 3.14, ...]$ which approaches $\pi$.
\vfill
\problem{}
Let $a_1 = 2$, and $a_{n+1} = 2 + \sqrt{a_n}$. \\
Show that the sequence $[a_n]$ is monotonically increasing and bounded above. Find its limit.
\begin{solution}
\textbf{$[a_n]$ is monotonically increasing:} Show this by induction. \\
\textbf{$[a_n]$ is bounded:} Induction again. Show that $\sqrt{a_n} < 2$. \\
\textbf{$\lim_{n \to\infty}a_n = 4$:} Use the fact that $\lim_{n\to\infty} a_n = \lim_{n\to\infty}a_{n+1}$, the hit the resulting equation with some algebra. Note that $1$ cannot be a solution, since $a_n \geq 2\ \forall n$.
\end{solution}
\vfill
\problem{}
Show that both assumptions of \ref{limexists} are necessary: \\
Find an example of a monotonically increasing sequence that does not have a limit, \\
and of a bounded sequence that does not have a limit.
\vfill
\definition{}
Let us provide a formal definition for a ``limit''. If you're stuck trying to prove something with this formal definition, give an informal explanation and come back to the problem later. \\
The number $A$ is the \textit{limit} of the sequence $[a_n]$ if for every positive real number $\epsilon < 0$, we can find a natural number N so that for all $n \geq N$, $|a_n - A| < \epsilon$. \\
If a sequence $[a_n]$ has a limit, we write $\lim_{n \to\infty}(a_n)$.
\vfill
\problem{}
Show that $0$ is the limit of $a_n = -\frac{1}{n}$, where $n \geq 1$. \\
Show that $\pi$ is the limit of the sequence $[3, 3.14, 3.141, ...]$.
\begin{solution}
$\lim_{n\to\infty}a_n = 0$ means that $\forall \epsilon > 0$, $\exists N \in \mathbb{N}$ so that $|a_n| < \epsilon\ \forall n < N$. \\
We know that for any $\epsilon$, $\exists p$ so that $\frac{1}{p} = \epsilon$. This is the \textit{Archemedian Property}. \\
It is now clear that $\lim_{n\to\infty}a_n = 0$
\linehack{}
$\lim_{n\to\infty}a_n = \pi$ means that $\forall \epsilon > 0$, $\exists N \in \mathbb{N}$ so that $|a_n - \pi| < \epsilon\ \forall n < N$. \\
Looking at the definition of this sequence, we get a similar ``Archemedian Property'': \\
$\forall \epsilon$, $\exists m$ so that $|a_m - \pi| < \epsilon$.
\end{solution}
\vfill
\problem{}
Show that if a sequence $[a_n]$ has a limit, that limit is unique. \\
This can be done by showing that if $A, B$ are both limits of $[a_n]$, $A$ and $B$ must be equal to $A$.
\begin{solution}
If both $A$ and $B$ are limits of $[a_n]$, we have the following: \\
$\forall \epsilon > 0$, $\exists N_A \in \mathbb{N}$ so that $|a_n - A| < \epsilon\ \forall n < N_A$. \\
$\forall \epsilon > 0$, $\exists N_B \in \mathbb{N}$ so that $|a_n - B| < \epsilon\ \forall n < N_B$. \\
Let $N = \max(N_A, N_B)$. \\
Then, $|a_n - A| + |a_n - B| < 2\epsilon\ \forall n > N$, \\
which can be writen as $|a_n - A| + |B - a_n| < 2\epsilon\ \forall n > N$. \\
By the triangle inequality, we have \\
$|a_n - A + B - a_n| \leq |a_n - A| + |B - a_n|$, \\
And since $|a_n - A + B - a_n| = |B - A|$, we have \\
$|B - A| < 2\epsilon\ \forall n > N$. \\
This should be true for all $\epsilon > 0$. \\
Let's set $\epsilon = \frac{|B-A|}{4}$, which is greater than zero iff $A \neq B$ \\
Then, $|B-A| < \frac{|B-A|}{2}$, which is impossible\textsuperscript{*}. \\
Therefore, if both $A$ and $B$ are limits of $[a_n]$, $A$ and $B$ must be equal.
\linehack{}
\textsuperscript{*}Note that we can also set $\epsilon = \frac{|B-A|}{2}$, which gives $|B-A| < |B-A|$. This is also false, and the proof still works. However, the extra $\frac{\hspace{2em}}{2}$ gives a clearer explanation.
\end{solution}
\vfill
\pagebreak
\section{Defining $e$}
\problem{}
Recall and prove the binomial theorem.
\input{parts/1 limits.tex}
\input{parts/2 e.tex}
\input{parts/3 more e.tex}
\begin{solution}
The binomial theorem:
$$(a + b)^n = \sum_{i=0}^{n} \binom{n}{i}a^ib^{n-i}$$
Prove this by induction, or however else you can.
\end{solution}
\vfill
\problem{}<e_n>
Prove the following:
$$ \bigg(1 + \frac{1}{n} \bigg)^n < 3 - \frac{1}{n}\ \text{for all } n = 3, 4, 5, ...$$
This proves that that the sequence $e_n = (1 + \frac{1}{n})^n$, $n = 1, 2, ...$ is bounded from above, \\
since $e_n < 3\ \forall n \in \mathbb{N}$.
\begin{solution}
$$
\bigg(1 + \frac{1}{n}\bigg)^n =
\sum_{k=0}^n \binom{n}{k}\frac{1}{n^i} =
2 + \sum_{k=2}^n \binom{n}{k}\frac{1}{n^i} =
2 + \sum_{k=2}^n \frac{1}{k!}\frac{(n)(n-1)...(n-k+1)}{n^k} <
2 + \sum_{k=2}^n \frac{1}{k!}
$$
$$
2 + \sum_{k=2}^n \frac{1}{k!} <
2 + \sum_{k=2}^n \frac{1}{k(k-1)} =
2 + 1 - \frac{1}{n} = 3 - \frac{1}{n}
$$
\end{solution}
\vfill
\theorem{Bernoulli's inequality}<bernoulli>
$(x + 1)^n \geq 1 + nx$ for $x \geq -1$ and $n \in \mathbb{N}$
\vfill
\problem{}
Use induction to prove \ref{bernoulli}
\vfill
\problem{}<e_n_inc>
Use \ref{bernoulli} to prove that the $[e_n]$ defined in \ref{e_n} is monotonically increasing.
\begin{solution}
We want to show that the following is true:
$$
\bigg(
1 + \frac{1}{n + 1}
\bigg)^{n+1}
>
\bigg(
1 + \frac{1}{n}
\bigg)^n
$$
Is inequality is equivalent to
$$
\Bigg(
\frac{
1 + \frac{1}{n+1}
}{
1 + \frac{1}{n}
}
\Bigg)^{n+1}
>
\bigg(
1 + \frac{1}{n}
\bigg)^{-1}
= \frac{1}{1 + \frac{1}{n}}
= \frac{n}{n+1}
= 1 - \frac{1}{n+1}
$$
Also,
$$
\frac{
1 + \frac{1}{n+1}
} {
1 + \frac{1}{n}
}
= 1 - \frac{1}{(n + 1)^2}
$$
\ref{theorem:bernoulli} tells us that
$$
\bigg(
1 - \frac{1}{(n+1)^2}
\bigg) ^ {n+1}
= 1 - \frac{n+1}{(n+1)^2}
= 1 - \frac{1}{n+1}
$$
Since this is equivalent to our original inequality, we are done.
\end{solution}
\vfill
\definition{}
\ref{e_n}, \ref{e_n_inc}, and \ref{limexists} tell us that $[e_n]$ has a limit. \\
Let us define $e$:
$$e = \lim_{n\to\infty}{e_n} = \lim_{n\to\infty}{\bigg(1 + \frac{1}{n} \bigg)^n}$$
\vfill
\section{Continuously compounding interest}
\problem{}
Derive the formula for $V(t)$ if the annual rate $r$ is compounded continuously.
\begin{solution}
For a rate $r$ compounded $n$ times per year, we have $V(t) = P(1 + \frac{r}{n})^{nt}$.
$\lim_{n\to\infty}{(V(t))} = \lim_{n\to\infty}{P(1 + \frac{r}{n})^{nt}}$
Let $a = \frac{n}{r}$ \\
$\lim_{n\to\infty}{a} = \infty$, so $\lim_{n\to\infty}{V(t)} = \lim_{a\to\infty}{V(t)}$ \\
Substituting $a$ for $n$, we get \\
$P(1 + \frac{r}{n})^{nt} = P(1 + \frac{1}{a})^{art}$ \\
And finally, we can evaluate \\
$\lim_{a\to\infty}{P (1 + \frac{1}{a})^{art}} = Pe^{rt}$
\end{solution}
\vfill
\pagebreak
\section{More about $e$}
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{1}{n+1}
\bigg)^n
= e
}
$$
\vfill
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{1}{n}
\bigg)^{n+1}
= e
}
$$
\vfill
\problem{}<inverse_e>
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 - \frac{1}{n}
\bigg)^n
= \frac{1}{e}
}
$$
\begin{solution}
$
\lim_{n\to\infty}{(1 - \frac{1}{n})^n} =
\lim_{n\to\infty}{(\frac{n-1}{n})^{(-1)(-n)}}
$ \\
$
= \lim_{n\to\infty}{(\frac{n}{n- 1 })^{-n}}
= \lim_{n\to\infty}{(1 + \frac{1}{n-1})^{-n}}
$ \\
$
= \lim_{n\to\infty}{{(1 + \frac{1}{n-1})^{(n-1)(\frac{n}{n-1})}}^{-1}}
$ \\
$
= \frac{1}{e}
$
\end{solution}
\vfill
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{x}{n}
\bigg)^n
= e^x
}
$$
Note that \ref{inverse_e} is a special case of this problem.
\vfill
\theorem{}
The following important formula is proven in most calculus courses.
$$e^x = \sum_{n=0}^{\infty}{\frac{x^n}{n!}} = 2 + \frac{x^2}{2!} + \frac{x^3}{3!} + ...$$
\vfill
\problem{}
What are the first six digits of $e$?
\begin{solution}
$e = 2.718\ 281\ 828$
\end{solution}
\vfill
\definition{}
If $f$ is a function, we say that $L$ is a limit of $f$ at $\infty$ if for every $\epsilon > 0$, we can find an $M \in \mathbb{R}$ so that $|f(x) - L| < \epsilon$ for $x > M$. \\
If this is true, we say that $L = \lim_{x\to\infty}{(f(x))}$.
\vfill
\problem{}
Prove the following: \\
Hint: If $x > 0$, then $\lfloor x \rfloor \leq x \leq \lceil x \rceil$
$$ \lim_{x\to\infty}{\bigg(1 + \frac{1}{x}\bigg)^x} = e$$
\vfill
\pagebreak
\section{$e$ and Probability}
\problem{}
A gambler plays a game $n$ times. Each time he plays, his chance of winning is $p$. What are the odds he will win exactly $k$ times?
\vfill
\problem{}
A gambler plays a game $10,000$ times. Each time he plays, he has a $\frac{1}{10,000}$ chance of winning. What are the odds he loses every time?
\vfill
\problem{}
$n$ people participate in a gift exchange. Each person puts their name in a hat, then names are drawn at random. For a large $n$, what is the probability that someone will draw their own name?
\vfill
\pagebreak
\end{document}

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\section{Limits}
\definition{Boundedness}
Let $a_1, a_2, a_3, ... $ (abbreviated $a_n$ in this handout) be a sequence of real numbers. \par
We say a number $u$ is an \textit{upper bound} of $a_n$ if $a_i \leq u ~ \forall i$. \par
If $a_n$ has an upper bound, we could say it is \textit{bounded from above}.
\definition{Monotonically increasing}
We say a sequence of real numbers $a_n$ is \textit{monotonically increasing} if $m < n \implies a_m < a_n$.
\definition{Limits (informal)}
The \textit{limit} of a sequence is a point to which the sequence gets \say{closer} to. \par
Not all sequences have limits. \par
Don't let this hand-wavy definition bother you too much, we'll see a proper definition soon.
\theorem{}<limexists>
Any monotonically increasing sequence that is bounded from above has a unique limit. \par
\vfill
\problem{}
Let $a_1 = 2$, and $a_{n+1} = 2 + \sqrt{a_n}$. \par
Show that the sequence $a_n$ is monotonically increasing and bounded above. Find its limit.
\begin{solution}
\textbf{$a_n$ is monotonically increasing:} Show this by induction. \par
\textbf{$a_n$ is bounded:} Induction again. Show that $\sqrt{a_n} < 2$. \par
\textbf{$\lim_{n \to\infty}a_n = 4$:} Use the fact that $\lim_{n\to\infty} a_n = \lim_{n\to\infty}a_{n+1}$, the hit the resulting equation with some algebra. Note that $1$ cannot be a solution, since $a_n \geq 2\ \forall n$.
\end{solution}
\vfill
\problem{}
Show that both assumptions of \ref{limexists} are necessary: \par
Find an example of a monotonically increasing sequence that does not have a limit, \par
and of a bounded sequence that does not have a limit.
\vfill
\pagebreak
\definition{Limits (formal)}
Let $a_n$ be a sequence.
$L$ is the \textit{limit} of this sequence if for any $\varepsilon < 0$, \par
we can find an $N$ so that $|a_n - L| < \varepsilon \forall n \geq N$.
\vfill
\problem{}
Show that $0$ is the limit of $a_n = \frac{1}{n}$, where $n \geq 1$. \par
Show that $\pi$ is the limit of the sequence $3,~ 3.1,~ 3.14,~ ...$.
\begin{solution}
$\lim_{n\to\infty}a_n = 0$ means that $\forall \epsilon > 0$, $\exists N \in \mathbb{N}$ so that $|a_n| < \epsilon\ \forall n < N$. \par
We know that for any $\epsilon$, $\exists p$ so that $\frac{1}{p} = \epsilon$. This is the \textit{Archemedian Property}. \par
It is now clear that $\lim_{n\to\infty}a_n = 0$
\linehack{}
$\lim_{n\to\infty}a_n = \pi$ means that $\forall \epsilon > 0$, $\exists N \in \mathbb{N}$ so that $|a_n - \pi| < \epsilon\ \forall n < N$. \par
Looking at the definition of this sequence, we get a similar ``Archemedian Property'': \par
$\forall \epsilon$, $\exists m$ so that $|a_m - \pi| < \epsilon$.
\end{solution}
\vfill
\problem{}
Show that if a sequence $a_n$ has a limit, that limit is unique. \par
\hint{Show that if $A, B$ are both limits of $a_n$, $A$ and $B$ must be equal.}
\begin{solution}
If both $A$ and $B$ are limits of $[a_n]$, we have the following: \par
$\forall \epsilon > 0$, $\exists N_A \in \mathbb{N}$ so that $|a_n - A| < \epsilon\ \forall n < N_A$. \par
$\forall \epsilon > 0$, $\exists N_B \in \mathbb{N}$ so that $|a_n - B| < \epsilon\ \forall n < N_B$. \par
Let $N = \max(N_A, N_B)$. \par
Then, $|a_n - A| + |a_n - B| < 2\epsilon\ \forall n > N$, \par
which can be writen as $|a_n - A| + |B - a_n| < 2\epsilon\ \forall n > N$. \par
By the triangle inequality, we have \par
$|a_n - A + B - a_n| \leq |a_n - A| + |B - a_n|$, \par
And since $|a_n - A + B - a_n| = |B - A|$, we have \par
$|B - A| < 2\epsilon\ \forall n > N$. \par
This should be true for all $\epsilon > 0$. \par
Let's set $\epsilon = \frac{|B-A|}{4}$, which is greater than zero iff $A \neq B$ \par
Then, $|B-A| < \frac{|B-A|}{2}$, which is impossible\textsuperscript{*}. \par
Therefore, if both $A$ and $B$ are limits of $[a_n]$, $A$ and $B$ must be equal.
\linehack{}
\textsuperscript{*}Note that we can also set $\epsilon = \frac{|B-A|}{2}$, which gives $|B-A| < |B-A|$. This is also false, and the proof still works. However, the extra $\frac{\hspace{2em}}{2}$ gives a clearer explanation.
\end{solution}
\vfill
\pagebreak

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\section{Defining $e$}
\problem{}
Recall and prove the binomial theorem.
\begin{solution}
The binomial theorem:
$$(a + b)^n = \sum_{i=0}^{n} \binom{n}{i}a^ib^{n-i}$$
We usually prove this by induction.
\end{solution}
\vfill
\problem{}<e_n>
Prove the following:
$$ \bigg(1 + \frac{1}{n} \bigg)^n < 3 - \frac{1}{n}\ \text{for all } n = 3, 4, 5, ...$$
This proves that that the sequence $e_n = (1 + \frac{1}{n})^n$, $n = 1, 2, ...$ is bounded from above, \par
since $e_n < 3\ \forall n \in \mathbb{N}$.
\begin{solution}
$$
\bigg(1 + \frac{1}{n}\bigg)^n =
\sum_{k=0}^n \binom{n}{k}\frac{1}{n^i} =
2 + \sum_{k=2}^n \binom{n}{k}\frac{1}{n^i} =
2 + \sum_{k=2}^n \frac{1}{k!}\frac{(n)(n-1)...(n-k+1)}{n^k} <
2 + \sum_{k=2}^n \frac{1}{k!}
$$
$$
2 + \sum_{k=2}^n \frac{1}{k!} <
2 + \sum_{k=2}^n \frac{1}{k(k-1)} =
2 + 1 - \frac{1}{n} = 3 - \frac{1}{n}
$$
\end{solution}
\vfill
\pagebreak
\theorem{Bernoulli's inequality}<bernoulli>
$(x + 1)^n \geq 1 + nx$ for $x \geq -1$ and $n \in \mathbb{N}$
\problem{}
Use induction to prove \ref{bernoulli}
\vfill
\problem{}<e_n_inc>
Use \ref{bernoulli} to prove that the $e_n$ defined in \ref{e_n} is monotonically increasing.
\begin{solution}
We want to show that the following is true:
$$
\bigg(
1 + \frac{1}{n + 1}
\bigg)^{n+1}
>
\bigg(
1 + \frac{1}{n}
\bigg)^n
$$
This inequality is equivalent to
$$
\Bigg(
\frac{
1 + \frac{1}{n+1}
}{
1 + \frac{1}{n}
}
\Bigg)^{n+1}
>
\bigg(
1 + \frac{1}{n}
\bigg)^{-1}
= \frac{1}{1 + \frac{1}{n}}
= \frac{n}{n+1}
= 1 - \frac{1}{n+1}
$$
Also,
$$
\frac{
1 + \frac{1}{n+1}
} {
1 + \frac{1}{n}
}
= 1 - \frac{1}{(n + 1)^2}
$$
\ref{bernoulli} tells us that
$$
\bigg(
1 - \frac{1}{(n+1)^2}
\bigg) ^ {n+1}
= 1 - \frac{n+1}{(n+1)^2}
= 1 - \frac{1}{n+1}
$$
Since this is equivalent to our original inequality, we are done.
\end{solution}
\vfill
\pagebreak
\definition{}
\ref{e_n}, \ref{e_n_inc}, and \ref{limexists} tell us that $e_n$ has a limit. \par
Let us define $e$:
$$e = \lim_{n\to\infty}{e_n} = \lim_{n\to\infty}{\bigg(1 + \frac{1}{n} \bigg)^n}$$
\vfill
\problem{}
Derive the formula for $V(t)$ if the annual rate $r$ is compounded continuously.
\begin{solution}
For a rate $r$ compounded $n$ times per year, we have $V(t) = P(1 + \frac{r}{n})^{nt}$.
$\lim_{n\to\infty}{(V(t))} = \lim_{n\to\infty}{P(1 + \frac{r}{n})^{nt}}$
Let $a = \frac{n}{r}$ \par
$\lim_{n\to\infty}{a} = \infty$, so $\lim_{n\to\infty}{V(t)} = \lim_{a\to\infty}{V(t)}$ \par
Substituting $a$ for $n$, we get \par
$P(1 + \frac{r}{n})^{nt} = P(1 + \frac{1}{a})^{art}$ \par
And finally, we can evaluate \par
$\lim_{a\to\infty}{P (1 + \frac{1}{a})^{art}} = Pe^{rt}$
\end{solution}
\vfill
\pagebreak

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\section{More about $e$}
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{1}{n+1}
\bigg)^n
= e
}
$$
\vfill
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{1}{n}
\bigg)^{n+1}
= e
}
$$
\vfill
\problem{}<inverse_e>
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 - \frac{1}{n}
\bigg)^n
= \frac{1}{e}
}
$$
\begin{solution}
$
\lim_{n\to\infty}{(1 - \frac{1}{n})^n} =
\lim_{n\to\infty}{(\frac{n-1}{n})^{(-1)(-n)}}
$ \par
$
= \lim_{n\to\infty}{(\frac{n}{n- 1 })^{-n}}
= \lim_{n\to\infty}{(1 + \frac{1}{n-1})^{-n}}
$ \par
$
= \lim_{n\to\infty}{{(1 + \frac{1}{n-1})^{(n-1)(\frac{n}{n-1})}}^{-1}}
$ \par
$
= \frac{1}{e}
$
\end{solution}
\vfill
\problem{}
Show that
$$
\lim_{n\to\infty}{
\bigg(
1 + \frac{x}{n}
\bigg)^n
= e^x
}
$$
Note that \ref{inverse_e} is a special case of this problem.
\vfill
\pagebreak
\theorem{}
The following important formula is proven in most calculus courses.
$$e^x = \sum_{n=0}^{\infty}{\frac{x^n}{n!}} = 2 + \frac{x^2}{2!} + \frac{x^3}{3!} + ...$$
\vfill
\problem{}
What are the first six digits of $e$?
\begin{solution}
$e = 2.718\ 281\ 828$
\end{solution}
\vfill
\definition{}
If $f$ is a function, we say that $L$ is a limit of $f$ at $\infty$ if for every $\epsilon > 0$, we can find an $M \in \mathbb{R}$ so that $|f(x) - L| < \epsilon$ for $x > M$. \par
If this is true, we say that $L = \lim_{x\to\infty}{(f(x))}$.
\vfill
\problem{}
Prove the following: \par
Hint: If $x > 0$, then $\lfloor x \rfloor \leq x \leq \lceil x \rceil$
$$ \lim_{x\to\infty}{\bigg(1 + \frac{1}{x}\bigg)^x} = e$$
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