Key Examples in Counting – IMT DeCal

# Key Examples in Counting

by Suraj Rampure

This note walks through a few selected examples of interesting problems in combinatorics. It also touches on the idea of combinatorial proofs.

## 1. Number of Factors

### How many factors does $1200$ have?

We could sit down and manually enumerate through all factors of 1200, one by one - 1, 2, 3, 4, 5, 6, … but that would take quite a bit of time. Instead, we will look at the prime factorization of 1200: $1200 = 2^4 \cdot 3 \cdot 5^2$.

We know each factor of 1200 will have some number of $2$s, some number of $3$s, and some number of $5$s. There are 5 options for the number of $2$s a factor could have: 0, 1, 2, 3 or 4 (meaning a factor of 1200 could either have a factor of $2^0$, or $2^1$, or $2^2$, or $2^3$, or $2^4$). Similarly, there are 2 options for the number of $3$s a factor could have (either 0 or 1) and 3 options for the number of $5$s (0, 1, or 2).

In other words, each factor will look like $2^a \cdot 3^b \cdot 5^c$, where $0 \leq a \leq 4$, $0 \leq b \leq 1$ and $0 \leq c \leq 2$.

Since we’re making three successive choices, we take the product of the number of choices at each step, yielding

$\text{number of factors of } 1200 = (4 + 1) (1 + 1) (2 + 1) = 30$

In general, if we have $n = p_1^{e_1} \cdot p_2^{e_2} \cdot … \cdot p_k^{e_k}$, the following holds:

$\boxed{\text{number of factors of } n = \prod_{i = 1}^k (e_i + 1) = (e_1 + 1) \cdot (e_2 + 1) \cdot ... \cdot (e_{k - 1} + 1) \cdot (e_k + 1)}$

We can also extend this problem.

### How many factors does 1200 have, that are multiples of 24?

We know each factor of 1200 will be of the form $2^a \cdot 3^b \cdot 5^c$. We now just need to determine the number of options we have for $a, b$ and $c$. Since $24 = 2^3 \cdot 3^1 \cdot 5^0$, we know that $a$ must be at least $3$ and $b$ must be at least $1$.

This restricts our set of choices: now, we have $3 \leq a \leq 4, 1 \leq b \leq 1$ and $0 \leq c \leq 2$. This means we have 2 choices for $a$ (3, 4), 1 choice for $b$ (1) and 3 for $c$ (0, 1, 2), yielding $2 \cdot 1 \cdot 3 = 6$ factors of 1200 that are multiples of 24.

## 2. Cardinality of the Power Set, Combinatorial Proofs

The power set $P(S)$ of a set $S$ is a set of all possible subsets of $S$. For example, if $S = {1, 2, 3}$, we have $P(S) = \{ \emptyset , \{1\}, \{2\}, \{3\}, \{1, 2\}, \{1, 3\}, \{2, 3\}, \{1, 2, 3\} \}$.

### If $S$ is a set such that $|S| = n$, what is $|P(S)|$?

When creating a subset of $S$, for each of the $n$ items in $S$, we have two options: either we include it in the subset, or do not include it in the subset. Since we have two options for each of the $n$ items, the total number of ways we can create a subset of $S$ is $2 \cdot 2 \cdot … \cdot 2 = 2^n$. Therefore,

$\boxed{|S| = n \implies |P(S)| = 2^n}$

It should be noted, however, that we can arrive at this result another way. Instead of looking at each element individually, and saying that for each element we have 2 options (include or exclude), we can look at all possible subsets. Let’s consider the example, $S = \{\text{dog}, \text{cat}, \text{zebra} \}$. Then, any subset will have size 0, 1, 2, or 3.

• There is ${3 \choose 0} = 1$ subset of size 0 - the empty set $\emptyset$
• There are ${3 \choose 1} = 3$ subsets of size 1 - $\{\text{dog}\}$, $\{\text{cat}\}$, $\{\text{zebra}\}$
• There are ${3 \choose 2} = 3$ subsets of size 2 - $\{\text{dog}, \text{cat}\}$, $\{\text{dog}, \text{zebra}\}$, $\{\text{cat}, \text{zebra}\}$
• There is ${3 \choose 3} = 1$ subset of size 3 - $\{\text{dog}, \text{cat}, \text{zebra}\}$

Thus, the total number of subsets of ${1, 2, 3}$ is ${3 \choose 0} + {3 \choose 1} + {3 \choose 2} + {3 \choose 3}$. However, using the relationship derived above, we have that there are $2^3$ subsets of size 3. This implies

${3 \choose 0} + {3 \choose 1} + {3 \choose 2} + {3 \choose 3} = 2^3$

This is not a co-incidence, and in fact, it holds in general (for $n \in \mathbb{N}$):

$\boxed{\sum_{i = 0}^n {n \choose i} = {n \choose 0} + {n \choose 1} + … + {n \choose n} = 2^n}$

To prove this more general statement, we can essentially repeat the argument we made for the $n = 3$ case, but for any $n$. Our argument is that both sides of the equals sign count the same quantity.

• The left hand side (LHS) counts the number of subsets of a set of size $n$ by finding the number of subsets of each size $k$, where $0 \leq k \leq n$, and then adding them together, yielding ${n \choose 0} + {n \choose 1} + … + {n \choose n}$
• The RHS reasons that for each of the $n$ elements, there are two choices when creating a subset – include or exclude – and thus there are $2^n$ subsets

Such an argument is known as a combinatorial proof, one where we reason that two expressions count the same quantity, and thus must be equal.

### How many sets are subsets of $S_1 = \{A, B, C, D, E\}$ or $S_2 = \{D, E, F, G\}$?

To attack this, we need the Principle of Inclusion-Exclusion. First, we can find the number subsets of $S_1$ and $S_2$ individually, and also the number of subsets of both.

$\text{# subsets of }S_1 \text{ or } S_2 = (\text{# subsets of } S_1) + (\text{# subsets of } S_2) - (\text{# subsets of both})$

There are $2^5$ subsets of $S_1$, and $2^4$ subsets of $S_2$. For a set to be a subset of both, it must be a subset of their intersection, $\{D, E\}$ – this set only has $2^2$ subsets. Then, the total number of subsets we are looking for is $2^5 + 2^4 - 2^2 = 44$.