# 9.5: Counting

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Counting? You already know how to count or you wouldn't be taking a college-level math class, right? Well yes, but what we'll really be investigating here are ways of counting efficiently. When we get to the probability situations a bit later in this chapter we will need to count some very large numbers, like the number of possible winning lottery tickets. One way to do this would be to write down every possible set of numbers that might show up on a lottery ticket, but believe me: you don't want to do this.

## Basic Counting

We will start, however, with some more reasonable sorts of counting problems in order to develop the ideas that we will soon need.

##### Example 21

Suppose at a particular restaurant you have three choices for an appetizer (soup, salad or breadsticks) and five choices for a main course (hamburger, sandwich, quiche, fajita or pizza). If you are allowed to choose exactly one item from each category for your meal, how many different meal options do you have?

###### Solution

Solution 1: One way to solve this problem would be to systematically list each possible meal:

$$\begin{array}{lll} \text{soup + hamburger} & \text{soup + sandwich} & \text{soup + quiche} \\ \text{soup + fajita} & \text{soup + pizza} & \text{salad + hamburger} \\ \text{salad + sandwich} & \text{salad + quiche} & \text{salad + fajita} \\ \text{salad + pizza} & \text{breadsticks + hamburger} & \text{breadsticks + sandwich} \\ \text{breadsticks + quiche} & \text{breadsticks + fajita} & \text{breadsticks + pizza} \end{array}$$

Assuming that we did this systematically and that we neither missed any possibilities nor listed any possibility more than once, the answer would be 15. Thus you could go to the restaurant 15 nights in a row and have a different meal each night.

Solution 2: Another way to solve this problem would be to list all the possibilities in a table:

$$\begin{array}{|l|l|l|l|l|l|} \hline & \textbf { hamburger } & \textbf { sandwich } & \textbf { quiche } & \textbf { fajita } & \textbf { pizza } \\ \hline \textbf { soup } & \text { Soup + burger } & & & & \\ \hline \textbf { salad } & \text { Salad + burger } & & & & \\ \hline \textbf { bread } & e t c . & & & & \\ \hline \end{array}$$

In each of the cells in the table we could list the corresponding meal: soup + hamburger in the upper left corner, salad + hamburger below it, etc. But if we didn't really care what the possible meals are, only how many possible meals there are, we could just count the number of cells and arrive at an answer of 15, which matches our answer from the first solution. (It's always good when you solve a problem two different ways and get the same answer!)

Solution 3: We already have two perfectly good solutions. Why do we need a third? The first method was not very systematic, and we might easily have made an omission. The second method was better, but suppose that in addition to the appetizer and the main course we further complicated the problem by adding desserts to the menu: we've used the rows of the table for the appetizers and the columns for the main courses—where will the desserts go? We would need a third dimension, and since drawing 3-D tables on a 2-D page or computer screen isn't terribly easy, we need a better way in case we have three categories to choose form instead of just two.

So, back to the problem in the example. What else can we do? Let's draw a tree diagram: This is called a "tree" diagram because at each stage we branch out, like the branches on a tree. In this case, we first drew five branches (one for each main course) and then for each of those branches we drew three more branches (one for each appetizer). We count the number of branches at the final level and get (surprise, surprise!) 15.

If we wanted, we could instead draw three branches at the first stage for the three appetizers and then five branches (one for each main course) branching out of each of those three branches.

OK, so now we know how to count possibilities using tables and tree diagrams. These methods will continue to be useful in certain cases, but imagine a game where you have two decks of cards (with 52 cards in each deck) and you select one card from each deck. Would you really want to draw a table or tree diagram to determine the number of outcomes of this game?

Let's go back to the previous example that involved selecting a meal from three appetizers and five main courses, and look at the second solution that used a table. Notice that one way to count the number of possible meals is simply to number each of the appropriate cells in the table, as we have done above. But another way to count the number of cells in the table would be multiply the number of rows (3) by the number of columns (5) to get 15. Notice that we could have arrived at the same result without making a table at all by simply multiplying the number of choices for the appetizer (3) by the number of choices for the main course (5). We generalize this technique as the basic counting rule:

##### Basic Counting Rule

If we are asked to choose one item from each of two separate categories where there are $$m$$ items in the first category and $$n$$ items in the second category, then the total number of available choices is $$m \cdot n$$

This is sometimes called the multiplication rule for probabilities.

##### Example 22

There are 21 novels and 18 volumes of poetry on a reading list for a college English course. How many different ways can a student select one novel and one volume of poetry to read during the quarter?

###### Solution

There are 21 choices from the first category and 18 for the second, so there are $$21 \cdot 18 = 378$$ possibilities.

The Basic Counting Rule can be extended when there are more than two categories by applying it repeatedly, as we see in the next example.

##### Example 23

Suppose at a particular restaurant you have three choices for an appetizer (soup, salad or breadsticks), five choices for a main course (hamburger, sandwich, quiche, fajita or pasta) and two choices for dessert (pie or ice cream). If you are allowed to choose exactly one item from each category for your meal, how many different meal options do you have?

###### Solution

There are 3 choices for an appetizer, 5 for the main course and 2 for dessert, so there are $$3 \cdot 5 \cdot 2=30$$ possibilities.

##### Example 24

A quiz consists of 3 true-or-false questions. In how many ways can a student answer the quiz?

###### Solution

There are 3 questions. Each question has 2 possible answers (true or false), so the quiz may be answered in $$2 \cdot 2 \cdot 2=8$$ different ways. Recall that another way to write $$2 \cdot 2 \cdot 2$$ is $$2^{3}$$ which is much more compact.

##### Try it Now 6

Suppose at a particular restaurant you have eight choices for an appetizer, eleven choices for a main course and five choices for dessert. If you are allowed to choose exactly one item from each category for your meal, how many different meal options do you have?

$$8 \cdot 11 \cdot 5=440$$ menu combinations

## Permutations

In this section we will develop an even faster way to solve some of the problems we have already learned to solve by other means. Let's start with a couple examples.

##### Example 25

How many different ways can the letters of the word MATH be rearranged to form a four-letter code word?

###### Solution

This problem is a bit different. Instead of choosing one item from each of several different categories, we are repeatedly choosing items from the same category (the category is: the letters of the word MATH) and each time we choose an item we do not replace it, so there is one fewer choice at the next stage: we have 4 choices for the first letter (say we choose A), then 3 choices for the second (M, T and H; say we choose H), then 2 choices for the next letter (M and T; say we choose M) and only one choice at the last stage (T). Thus there are $$4 \cdot 3 \cdot 2 \cdot 1=24$$ ways to spell a code worth with the letters MATH.

In this example, we needed to calculate $$n \cdot(n-1) \cdot(n-2) \cdots 3 \cdot 2 \cdot 1$$. This calculation shows up often in mathematics, and is called the factorial, and is notated $$n$$!

##### Factorial

$$n !=n \cdot(n-1) \cdot(n-2) \cdots 3 \cdot 2 \cdot 1$$

##### Example 26

How many ways can five different door prizes be distributed among five people?

###### Solution

There are 5 choices of prize for the first person, 4 choices for the second, and so on. The number of ways the prizes can be distributed will be $$5 !=5 \cdot 4 \cdot 3 \cdot 2 \cdot 1=120$$ ways.

Now we will consider some slightly different examples.

##### Example 27

###### Solution

In order to compute the probability, we need to count the total number of ways six numbers can be drawn, and the number of ways the six numbers on the player’s ticket could match the six numbers drawn from the machine. Since there is no stipulation that the numbers be in any particular order, the number of possible outcomes of the lottery drawing is $$_{48} C_{6}=12,271,512$$. Of these possible outcomes, only one would match all six numbers on the player’s ticket, so the probability of winning the grand prize is:

$$\frac{_6 C_{6}}{_{48} C_{6}}=\frac{1}{12271512} \approx 0.0000000815$$

##### Example 36

In the state lottery from the previous example, if five of the six numbers drawn match the numbers that a player has chosen, the player wins a second prize of \$1,000. Compute the probability that you win the second prize if you purchase a single lottery ticket.

###### Solution

As above, the number of possible outcomes of the lottery drawing is $$_{48} C_{6}=12,271,512$$. In order to win the second prize, five of the six numbers on the ticket must match five of the six winning numbers; in other words, we must have chosen five of the six winning numbers and one of the 42 losing numbers. The number of ways to choose 5 out of the 6 winning numbers is given by $$_{6} C_{5}=6$$ and the number of ways to choose 1 out of the 42 losing numbers is given by $$_{42} C_{1}=42$$. Thus the number of favorable outcomes is then given by the Basic Counting Rule: $$_{6} C_{5} \cdot_{42} C_{1}=6 \cdot 42=252$$. So the probability of winning the second prize is.

$$\frac{\left(_{6} C_{5}\right)\left(_{42} C_{1}\right)}{_{48} C_{6}}=\frac{252}{12271512} \approx 0.0000205$$

##### Try it Now 9

A multiple-choice question on an economics quiz contains 10 questions with five possible answers each. Compute the probability of randomly guessing the answers and getting 9 questions correct.

There are $$5^{10}=9,765,625$$ different ways the exam can be answered. There are 10 possible locations for the one missed question, and in each of those locations there are 4 wrong answers, so there are 40 ways the test could be answered with one wrong answer.

$$\mathrm{P}(9 \text { answers correct })=\frac{40}{5^{10}} \approx 0.0000041$$ chance

##### Example 37

Compute the probability of randomly drawing five cards from a deck and getting exactly one Ace.

###### Solution

In many card games (such as poker) the order in which the cards are drawn is not important (since the player may rearrange the cards in his hand any way he chooses); in the problems that follow, we will assume that this is the case unless otherwise stated. Thus we use combinations to compute the possible number of 5-card hands, $$_{52} C_{5}$$. This number will go in the denominator of our probability formula, since it is the number of possible outcomes.

For the numerator, we need the number of ways to draw one Ace and four other cards (none of them Aces) from the deck. Since there are four Aces and we want exactly one of them, there will be $$_4 C_{1}$$ ways to select one Ace; since there are 48 non-Aces and we want 4 of them, there will be $$_{48} C_{4}$$\) ways to select the four non-Aces. Now we use the Basic Counting Rule to calculate that there will be $$_{4} C_{1} \cdot _{48} C_{4}$$ ways to choose one ace and four non-Aces.

Putting this all together, we have

$$P(\text {one Ace} )=\frac{\left(_{4} C_{1}\right)\left(_{48} C_{4}\right)}{_{52} C_{5}}=\frac{778320}{2598960} \approx 0.299$$

##### Example 38

Compute the probability of randomly drawing five cards from a deck and getting exactly two Aces.

###### Solution

The solution is similar to the previous example, except now we are choosing 2 Aces out of 4 and 3 non-Aces out of 48; the denominator remains the same:

$$P(\text {two Aces})=\frac{\left(_{4} C_{2}\right)\left(_{48} C_{3}\right)}{_{52} C_{5}}=\frac{103776}{2598960} \approx 0.0399$$

It is useful to note that these card problems are remarkably similar to the lottery problems discussed earlier.

##### Try it Now 10

Compute the probability of randomly drawing five cards from a deck of cards and getting three Aces and two Kings.

$$P(\text {three Aces and two Kings})=\frac{\left(_{4} C_{3}\right)\left(_{4} C_{2}\right)}{_{52} C_{5}}=\frac{24}{2598960} \approx 0.0000092$$

## Birthday Problem

Let's take a pause to consider a famous problem in probability theory:

Suppose you have a room full of 30 people. What is the probability that there is at least one shared birthday?

Take a guess at the answer to the above problem. Was your guess fairly low, like around 10%? That seems to be the intuitive answer ($$\frac{30}{365}$$, perhaps?). Let's see if we should listen to our intuition. Let's start with a simpler problem, however.

##### Example 39

Suppose three people are in a room. What is the probability that there is at least one shared birthday among these three people?

###### Solution

There are a lot of ways there could be at least one shared birthday. Fortunately there is an easier way. We ask ourselves “What is the alternative to having at least one shared birthday?” In this case, the alternative is that there are no shared birthdays. In other words, the alternative to “at least one” is having none. In other words, since this is a complementary event,

$$P(\text {at least one})=1-P(\text {none})$$

We will start, then, by computing the probability that there is no shared birthday. Let's imagine that you are one of these three people. Your birthday can be anything without conflict, so there are 365 choices out of 365 for your birthday. What is the probability that the second person does not share your birthday? There are 365 days in the year (let's ignore leap years) and removing your birthday from contention, there are 364 choices that will guarantee that you do not share a birthday with this person, so the probability that the second person does not share your birthday is $$\frac{364}{365}$$. Now we move to the third person. What is the probability that this third person does not have the same birthday as either you or the second person? There are 363 days that will not duplicate your birthday or the second person's, so the probability that the third person does not share a birthday with the first two is $$\frac{363}{365}$$.

We want the second person not to share a birthday with you and the third person not to share a birthday with the first two people, so we use the multiplication rule:

$$P(\text {no shared birthday})=\frac{365}{365} \cdot \frac{364}{365} \cdot \frac{363}{365} \approx 0.9918$$

and then subtract from 1 to get

$$P(\text {shared birthday})=1-P(\text {no shared birthday})=1-0.9918=0.0082$$.

This is a pretty small number, so maybe it makes sense that the answer to our original problem will be small. Let's make our group a bit bigger.

##### Example 40

Suppose five people are in a room. What is the probability that there is at least one shared birthday among these five people?

###### Solution

Continuing the pattern of the previous example, the answer should be

$$P(\text {shared birthday})=1-\frac{365}{365} \cdot \frac{364}{365} \cdot \frac{363}{365} \cdot \frac{362}{365} \cdot \frac{361}{365} \approx 0.0271$$

Note that we could rewrite this more compactly as

$$P(\text {shared birthday})=1-\frac{_{365}P_5}{365^{5}} \approx 0.0271$$

which makes it a bit easier to type into a calculator or computer, and which suggests a nice formula as we continue to expand the population of our group.

##### Example 41

Suppose 30 people are in a room. What is the probability that there is at least one shared birthday among these 30 people?

###### Solution

Here we can calculate

$$P(\text { shared birthday })=1-\frac{_{365}P_{30}}{365^{30}} \approx 0.706$$

which gives us the surprising result that when you are in a room with 30 people there is a 70% chance that there will be at least one shared birthday!

If you like to bet, and if you can convince 30 people to reveal their birthdays, you might be able to win some money by betting a friend that there will be at least two people with the same birthday in the room anytime you are in a room of 30 or more people. (Of course, you would need to make sure your friend hasn't studied probability!) You wouldn't be guaranteed to win, but you should win more than half the time.

This is one of many results in probability theory that is counterintuitive; that is, it goes against our gut instincts. If you still don't believe the math, you can carry out a simulation. Just so you won't have to go around rounding up groups of 30 people, someone has kindly developed a Java applet so that you can conduct a computer simulation. Go to this web page: http://statweb.stanford.edu/~susan/surprise/Birthday.html, and once the applet has loaded, select 30 birthdays and then keep clicking Start and Reset. If you keep track of the number of times that there is a repeated birthday, you should get a repeated birthday about 7 out of every 10 times you run the simulation.

##### Try it Now 11

Suppose 10 people are in a room. What is the probability that there is at least one shared birthday among these 10 people?

$$P(\text {shared birthday})=1-\frac{_{365}P_{10}}{365^{10}} \approx 0.117$$