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Lesson 2: Counting Methods

Module 3: Probability Basics • Lesson 2 of 4 • ~35-40 minutes

← Previous: Intro to Probability Lesson 2 of 4 Next: Conditional Probability →

Learning Objectives

By the end of this lesson, you will be able to:

  • Apply the Fundamental Counting Principle to count outcomes
  • Calculate factorials and understand their use in counting
  • Use permutations when order matters
  • Use combinations when order doesn't matter
  • Decide which counting method to use for different situations

Why Counting Methods Matter

In Lesson 1, we used P(A) = n(A) / n(S) to calculate probabilities. But what if the sample space has hundreds or thousands of outcomes? Listing them all is impractical!

Counting methods let us systematically count outcomes without listing every single one. This is essential for:

Fundamental Counting Principle

Fundamental Counting Principle (FCP)

If one event can occur in m ways and a second event can occur in n ways, then the two events together can occur in m × n ways.

Extended: If there are k events that can occur in n₁, n₂, ..., n_k ways respectively, then the total number of ways all k events can occur is:

n₁ × n₂ × n₃ × ... × n_k

Example 1: Outfit Combinations

Question: You have 4 shirts and 3 pairs of pants. How many different outfits can you make?

Solution:

  1. Choose a shirt: 4 ways
  2. Choose pants: 3 ways
  3. Total outfits = 4 × 3 = 12

Example 2: License Plates

Question: A license plate consists of 2 letters followed by 3 digits. How many different plates are possible?

Solution:

  1. First letter: 26 choices (A-Z)
  2. Second letter: 26 choices
  3. First digit: 10 choices (0-9)
  4. Second digit: 10 choices
  5. Third digit: 10 choices
  6. Total = 26 × 26 × 10 × 10 × 10 = 676,000 plates

Example 3: Restaurant Menu

Question: A restaurant offers 5 appetizers, 8 main courses, and 4 desserts. How many different three-course meals can you order?

Solution:

Total meals = 5 × 8 × 4 = 160 possible three-course meals

Factorials

Factorial (n!)

The factorial of a positive integer n, written as n!, is the product of all positive integers from 1 to n.

n! = n × (n−1) × (n−2) × ... × 3 × 2 × 1

Special case: 0! = 1 (by definition)

Examples of Factorials:

  • 3! = 3 × 2 × 1 = 6
  • 4! = 4 × 3 × 2 × 1 = 24
  • 5! = 5 × 4 × 3 × 2 × 1 = 120
  • 10! = 10 × 9 × 8 × 7 × 6 × 5 × 4 × 3 × 2 × 1 = 3,628,800

Note: Factorials grow very rapidly! Use a calculator for factorials larger than 5!

Calculator Tip

Most calculators have an "n!" or "x!" button. Use it for large factorials!

Example: To calculate 10!, press: 10, then the factorial button

Permutations (Order Matters)

Permutation

A permutation is an arrangement of objects where order matters.

Example: Arranging 3 books on a shelf. The order "ABC" is different from "BAC".

Permutations of n Objects

Number of ways to arrange n distinct objects:

n!

Example 4: Arranging Books

Question: How many ways can you arrange 5 different books on a shelf?

Solution:

Number of arrangements = 5! = 5 × 4 × 3 × 2 × 1 = 120 ways

Permutations of r Objects from n (P(n,r) or nPr)

Number of ways to arrange r objects chosen from n distinct objects:

P(n,r) = n! / (n−r)!

Alternative notation: nPr or nPr

Example 5: Race Podium

Question: In a race with 10 runners, how many ways can gold, silver, and bronze medals be awarded?

Solution:

We're choosing 3 runners from 10, and order matters (gold ≠ silver ≠ bronze)

P(10,3) = 10! / (10−3)! = 10! / 7!

= (10 × 9 × 8 × 7!) / 7!

= 10 × 9 × 8 = 720 ways

Example 6: Password Creation

Question: How many 4-letter passwords can be formed from the letters A through F if no letter can be repeated?

Solution:

We're arranging 4 letters from 6, and order matters

P(6,4) = 6! / (6−4)! = 6! / 2!

= (6 × 5 × 4 × 3 × 2!) / 2!

= 6 × 5 × 4 × 3 = 360 passwords

Shortcut for Permutations

Instead of calculating the full factorial, just multiply the first few terms:

P(n,r) = n × (n−1) × (n−2) × ... × (n−r+1)

Example: P(10,3) = 10 × 9 × 8 = 720

Combinations (Order Doesn't Matter)

Combination

A combination is a selection of objects where order does NOT matter.

Example: Choosing 3 people for a committee. The group {Alice, Bob, Carol} is the same as {Carol, Alice, Bob}.

Number of ways to choose r objects from n distinct objects (order doesn't matter):

C(n,r) = n! / (r! × (n−r)!)

Alternative notation: nCr, nCr, or "n choose r"

Relationship Between Permutations and Combinations

C(n,r) = P(n,r) / r!

Why? When order doesn't matter, we divide by r! to remove duplicate arrangements.

Example 7: Committee Selection

Question: How many ways can you choose 3 people from a group of 8 to form a committee?

Solution:

Order doesn't matter (committee has no ranks), so we use combinations

C(8,3) = 8! / (3! × 5!)

= (8 × 7 × 6 × 5!) / (3! × 5!)

= (8 × 7 × 6) / (3 × 2 × 1)

= 336 / 6 = 56 ways

Example 8: Lottery

Question: In a lottery, you must choose 6 numbers from 1 to 49. How many different combinations are possible?

Solution:

Order doesn't matter, so we use combinations

C(49,6) = 49! / (6! × 43!)

= (49 × 48 × 47 × 46 × 45 × 44) / (6 × 5 × 4 × 3 × 2 × 1)

= 10,068,347,520 / 720 = 13,983,816 combinations

(That's why winning the lottery is so unlikely!)

Example 9: Choosing Toppings

Question: A pizza shop offers 10 toppings. How many ways can you choose exactly 4 toppings?

Solution:

Order doesn't matter (same pizza regardless of topping order)

C(10,4) = 10! / (4! × 6!)

= (10 × 9 × 8 × 7) / (4 × 3 × 2 × 1)

= 5,040 / 24 = 210 ways

Permutations vs. Combinations: Decision Guide

Which Method Should I Use?

Question Does Order Matter? Method Formula
Race winners (1st, 2nd, 3rd) YES Permutation P(n,r)
Committee members NO Combination C(n,r)
Password letters YES Permutation P(n,r)
Lottery numbers NO Combination C(n,r)
Seating arrangement YES Permutation n! or P(n,r)
Selecting items from a menu NO Combination C(n,r)

Key Question to Ask:

"If I swap two items, do I get a different outcome?"

  • YES (different outcome) → Order matters → Permutation
  • NO (same outcome) → Order doesn't matter → Combination

Check Your Understanding

Practice Question 1

A restaurant has 3 appetizers, 5 entrees, and 4 desserts. How many different complete meals can be ordered?

Solution:

Use Fundamental Counting Principle:

Total meals = 3 × 5 × 4 = 60 complete meals

Practice Question 2

Calculate 6!

Solution:

6! = 6 × 5 × 4 × 3 × 2 × 1 = 720

Practice Question 3

How many ways can 4 students be arranged in a row for a photo?

Solution:

Order matters (different positions = different photo)

Number of arrangements = 4! = 24 ways

Practice Question 4

From a class of 12 students, how many ways can a teacher choose a president, vice president, and secretary?

Solution:

Order matters (president ≠ vice president ≠ secretary)

Use permutation: P(12,3) = 12 × 11 × 10 = 1,320 ways

Practice Question 5

How many ways can you choose 5 cards from a standard 52-card deck?

Solution:

Order doesn't matter (a hand is the same regardless of order dealt)

Use combination: C(52,5) = 52! / (5! × 47!)

= (52 × 51 × 50 × 49 × 48) / (5 × 4 × 3 × 2 × 1)

= 311,875,200 / 120 = 2,598,960 ways

Practice Question 6

Should you use a permutation or combination? You're selecting 3 books from 10 to take on vacation.

Answer: Combination

Reasoning:

Order doesn't matter. Whether you choose Book A, Book B, Book C or Book C, Book A, Book B, you're taking the same 3 books.

C(10,3) = (10 × 9 × 8) / (3 × 2 × 1) = 720 / 6 = 120 ways

Key Takeaways

  • Fundamental Counting Principle: Multiply the number of ways each event can occur
  • Factorial n!: Product of integers from 1 to n (grows rapidly!)
  • Permutations P(n,r): Use when ORDER MATTERS → n!/(n−r)!
  • Combinations C(n,r): Use when ORDER DOESN'T MATTER → n!/(r!(n−r)!)
  • Key question: "Does swapping items create a different outcome?" Yes = permutation, No = combination
  • C(n,r) = P(n,r) / r! (combinations remove duplicate orderings)

What's Next?

You now have powerful tools for counting outcomes! In Lesson 3: Conditional Probability & Independence, you'll learn how probabilities change when you have partial information.

Coming up: P(A|B), multiplication rule, independent vs. dependent events

← Previous: Intro to Probability Module Home Next: Conditional Probability →