\section{Proofs by Induction} \definition{} The last proof technique we'll discuss in this handout is \textit{induction.} \par This is particularly useful when we have a \say{countable} variable, usually an integer. \par Let's say we're proving a statement $A$ for all positive integers $n$. \par We'll write the special case \say{$A$ holds for $n$} as $A_n$. \vspace{2mm} A proof by induction consists of two parts: a \textit{base case} and a \textit{inductive step}. \par The base case is usually fairly simple: we show that our statement holds for $n = 0$. \par In other words, the base case shows that $A_0$ is true. The inductive step is a bit more confusing: we show that if our statement holds for $n$, it must hold for $n = 1$. In other words, we show that $A_n \implies A_{n + 1}$. \vspace{2mm} In this way, we build an infinite implication chain: \par The base case proves that $A_0$. By the inductive step, $A_0 \implies A_1$, $A_1 \implies A_2$, and so on. \par We can thus conclude that $A_n$ is true for all $n \in \{0, 1, 2, 3, ...\}$ \problem{} Proof by induction will make a bit more sense with an example. \par Read and understand the following proof. \begin{examplesolution} Show that $1 + 2 + ... + n = \frac{n(n+1)}{2}$ \linehack{} \textbf{Base case:} $n = 1$ \par Substitute $n = 1$ into the hypothesis: $1 \qe \frac{1(1 + 1)}{2}$ \par but we have that $\frac{1(1 + 1)}{2} = \frac{2}{2} = 1$, so this is of course true. \vspace{2mm} \textbf{Inductive step:} \par Now, we assume our hypothesis is true for $n$, \par and show it is true for $n + 1$. \vspace{2mm} Write the hypothesis for $n + 1$: $$ 1 + 2 + ... + n + (n + 1) \qe \frac{(n+1)(n+2)}{2} $$ We know that $1 + 2 + ... + n = \frac{n(n+1)}{2}$, so: $$ 1 + 2 + ... + n + (n + 1) = \frac{n(n+1)}{2} + (n+1) $$ now we can complete the proof with some algebra: $$ \frac{n(n+1)}{2} + (n+1) = \frac{n(n+1) + 2(n+1)}{2} = \frac{(n + 2)(n+1)}{2} $$ So, we've shown that the $n^\text{th}$ case implies the $(n+1)^\text{th}$ case.\par We're therefore done, the hypothesis is true for $n \in \{1, 2, 3, ...\}$ \end{examplesolution} \vfill \pagebreak \problem{} Why do we need a base case when constructing a proof by induction? \par \hint{Try to prove that $n = n + 1$ for all $n \in \mathbb{Z}^+$} \begin{solution} Consider the following example: \par Say we want to prove that $n = n + 1$ for all $n \in \mathbb{Z}^+$. \vspace{2mm} \textbf{Inductive step:} Assume our hypothesis is true for $n$ (that is $n = n + 1$). Is this true for $n + 1$? \par Adding 1 to both sides, we get $n+1=n+1+1$, which means that $(n+1)=(n+1)+1$, which is the statement we wanted to prove. We've thus completed the inductive step! \vspace{2mm} Our problem is as follows: we've shown that $A_1 \implies A_2 \implies ...$, but we have no reason to believe that $A_1$ is true. If it was, our hypothesis would be correct---but since it isn't, this is not a complete proof. \end{solution} \vfill \problem{} Show that $1^2 + 2^2 + 3^3 + ... + n^2 = \frac{1}{6}(n)(n+1)(2n+1)$. \begin{solution} \textbf{Base case:}\par $1^2 = \frac{1}{6}(1)(1+1)(2 + 1) = 1$, which is true. \vspace{2mm} \textbf{Induction:}\par Assume $1^2 + ... + n^2$ satisfies the equation above. \par $$ 1^2 + 2^2 + ... + n^2 + (n+1)^2 = \frac{(n)(n+1)(2n+1)}{6} + (n + 1)^2 $$ which is equal to $$ \frac{(n)(n+1)(2n+1) + 6(n+1)^2}{6} $$ now expand and factor to get $$ \frac{(n+1)(n+2)(2(n+1)+1)}{6} $$ \end{solution} \vfill \problem{} Show that $2^n - 1$ is divisible by 3 for all odd $n$ \par \hint{If $n$ is odd, the next odd number is $n + 2$.} \begin{solution} \textbf{Base case:} \par $2^2 - 1 = 3$, which is divisible by 3.. \vspace{2mm} \textbf{Induction:}\par Assume $2^n - 1$ is divisible by 3. \par $2^{(n+2)} - 1 = 4(2^n) - 1 = 4(2^n - 1) + 3$ \par By our induction hypothesis, $(2^n - 1)$ has a factor of 3. \par Therefore, $4(2^n - 1) + 3$ must also have a factor of 3. \end{solution} \vfill \pagebreak \definition{} As you may already know, \say{n choose k} is defined as follows: \par $$ \binom{n}{k} = \frac{n!}{k!(n-k)!} $$ This counts the number of ways to choose $k$ things from a set of $n$, disregarding the order of the chosen items. \theorem{Pascal's Identity} The binomial coefficient defined above satisfies the following equality: $$ \binom{n+1}{k} = \binom{n}{k-1} \times \binom{n}{k} $$ \problem{} Using induction, show that $$ \binom{n}{0} + \binom{n}{1} + ... + \binom{n}{n} = 2^n. $$ \vfill Note that although induction is a powerful proof technique, it usually leads to uninteresting results. \par If we prove a statement using induction, we conclude that it is true---but we get very little insight on \textit{why} it is true. \vspace{2mm} Alternative proofs are take a bit more work than inductive proofs, but they are much more valuable. \par For example, see the proof of the statement in \ref{binomsum} on the next page. \pagebreak \makeatletter \@makeORMCbox{tmpbox}{Alternative Proof}{ogrape!10!white}{ogrape} \makeatother \begin{tmpbox} Consider the following problem: \par How many ways are there to write a number $x$ as an ordered sum of positive integers? \par \note{ An \say{ordered sum} means that the order of numbers in the sum matters. \\ For example, if $x = 5$, we will consider $4 + 1$ and $1 + 4$ as distinct sums. } \vspace{2mm} First, we'll think of $x$ as an array of $1$s which we want to group into positive integers. If $x = 3$, We have $x = 1~1~1$, which we can group as $1+1+1$,~ $(1+1) + 1$,~ $1 + (1+1)$,~ and $(1+1+1)$. \linehack{} \textbf{Solution 1:}\par One way to solve this is to use the usual \say{stars and bars} method, \par where we count the number of ways we can place $n$ \say{bars} between $x$ \say{stars}. Each bar corresponds to a \say{$+$} in the array of ones. \par \note[Note]{Convince yourself that there are $\binom{x-1}{n}$ ways to place $n$ bars between $x$ objects.} If we add the number of ways to write $x$ as a sum of $n \in \{1, 2, ..., x\}$ integers, we get: $$ \sum_{n = 1}^{x-1} \binom{x-1}{n} = \binom{x-1}{0} + \binom{n}{1} + ... + \binom{x-1}{x-1} $$ \linehack{} \textbf{Solution 2:}\par We could also observe that there are $x - 1$ places to put a \say{bar} in the array of ones. This corresponds to $x - 1$ binary positions, and thus $2^{x-1}$ ways to seperate our array of $1$s with bars. \linehack{} \textbf{Conclusion:}\par We've found that the number of ways to split $x$ can be written as either $\sum_{n = 1}^{x-1} \binom{x-1}{n}$ or $2^{x-1}$, and therefore $\sum_{n = 1}^{x-1} \binom{x-1}{n} = 2^{x-1}$. \end{tmpbox} \pagebreak