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Lesson 1: Introduction to Probability

Module 3: Probability Basics • Lesson 1 of 4 • ~30-35 minutes

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Learning Objectives

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

  • Define probability and explain what it measures
  • Identify sample spaces and events for probability experiments
  • Calculate basic probabilities using the classical approach
  • Apply fundamental probability rules (0 ≤ P(A) ≤ 1, complement rule)
  • Use probability notation correctly

What is Probability?

Probability

Probability is a numerical measure of the likelihood that an event will occur. It quantifies uncertainty with a number between 0 and 1.

Probability helps us answer questions like:

The Probability Scale

  • P = 0: Event is impossible (will never happen)
  • P = 0.5: Event has a 50-50 chance (equally likely to happen or not)
  • P = 1: Event is certain (will definitely happen)
  • 0 < P < 1: Event is possible but not certain

Key Terminology

Experiment

An experiment (or trial) is any process that generates well-defined outcomes.

Examples: Flipping a coin, rolling a die, drawing a card, measuring someone's height

Outcome

An outcome is a single result of an experiment.

Examples: Getting "heads" on a coin flip, rolling a "5" on a die

Sample Space (S)

The sample space is the set of all possible outcomes of an experiment.

Examples of Sample Spaces:

Experiment Sample Space (S)
Flip a coin S = {Heads, Tails}
Roll a six-sided die S = {1, 2, 3, 4, 5, 6}
Draw a card from a standard deck S = {52 different cards}
Count students in a class S = {0, 1, 2, 3, ...}

Event

An event is a collection of one or more outcomes from the sample space. We usually denote events with capital letters like A, B, C.

Example: Rolling a Die

Sample Space: S = {1, 2, 3, 4, 5, 6}

Possible Events:

  • Event A = "Rolling an even number" = {2, 4, 6}
  • Event B = "Rolling a number greater than 4" = {5, 6}
  • Event C = "Rolling a 3" = {3}

Calculating Probability: The Classical Approach

Classical Probability Formula

P(A) = (Number of outcomes in event A) / (Total number of outcomes in S)

P(A) = n(A) / n(S)

Where: n(A) = number of outcomes in event A, n(S) = total outcomes in sample space

Important: This formula only works when all outcomes are equally likely!

Examples where it works: Fair coin, fair die, randomly selected card

Examples where it doesn't work: Weighted die, biased coin

Example 1: Rolling a Fair Die

Question: What is the probability of rolling a number greater than 4?

Solution:

  1. Sample Space: S = {1, 2, 3, 4, 5, 6}, so n(S) = 6
  2. Event A: "Rolling greater than 4" = {5, 6}, so n(A) = 2
  3. Calculate: P(A) = n(A) / n(S) = 2 / 6 = 1/3 ≈ 0.333

Answer: The probability is 1/3 or about 33.3%

Example 2: Drawing a Card

Question: What is the probability of drawing a heart from a standard deck?

Solution:

  1. Sample Space: A standard deck has 52 cards, so n(S) = 52
  2. Event B: "Drawing a heart" – there are 13 hearts, so n(B) = 13
  3. Calculate: P(B) = n(B) / n(S) = 13 / 52 = 1/4 = 0.25

Answer: The probability is 1/4 or 25%

Example 3: Flipping Two Coins

Question: What is the probability of getting exactly one head when flipping two coins?

Solution:

  1. Sample Space: S = {HH, HT, TH, TT}, so n(S) = 4
  2. Event C: "Exactly one head" = {HT, TH}, so n(C) = 2
  3. Calculate: P(C) = n(C) / n(S) = 2 / 4 = 1/2 = 0.5

Answer: The probability is 1/2 or 50%

Fundamental Probability Rules

Rule 1: Range of Probabilities

0 ≤ P(A) ≤ 1

Meaning: Every probability must be between 0 and 1 (inclusive).

  • If P(A) < 0 or P(A) > 1, you made a mistake!
  • Probabilities can be written as decimals (0.25), fractions (1/4), or percentages (25%)

Rule 2: Probability of the Sample Space

P(S) = 1

Meaning: The probability that something in the sample space occurs is 1 (certainty).

Example: When you roll a die, you're guaranteed to get 1, 2, 3, 4, 5, or 6. So P(getting any number) = 1

Rule 3: Probability of an Impossible Event

P(∅) = 0

Meaning: The probability of an impossible event (empty set) is 0.

Example: The probability of rolling a 7 on a standard six-sided die is 0.

Rule 4: Complement Rule

P(not A) = 1 − P(A)

OR: P(A') = 1 − P(A)

Meaning: The probability that event A does NOT occur equals 1 minus the probability that A does occur.

Notation: "not A" can be written as A', Ā, or Ac (complement of A)

Why the Complement Rule is Useful

Sometimes it's easier to calculate P(not A) than P(A)!

Example: "What's the probability of getting at least one head in 3 coin flips?"

  • Direct method: Count outcomes with 1, 2, or 3 heads (complicated!)
  • Complement method: P(at least one head) = 1 − P(no heads) = 1 − (1/8) = 7/8 (easier!)

Example 4: Using the Complement Rule

Question: If the probability of rain tomorrow is 0.35, what is the probability it will NOT rain?

Solution:

Let A = "it rains tomorrow"

P(A) = 0.35

P(not A) = 1 − P(A) = 1 − 0.35 = 0.65

Answer: The probability it won't rain is 0.65 or 65%

Example 5: Complement with Cards

Question: What is the probability of NOT drawing a face card (Jack, Queen, King) from a standard deck?

Solution:

  1. There are 12 face cards in a deck (4 suits × 3 face cards)
  2. P(face card) = 12/52 = 3/13
  3. P(not a face card) = 1 − P(face card) = 1 − 3/13 = 10/13 ≈ 0.769

Answer: The probability is 10/13 or about 76.9%

Check Your Understanding

Practice Question 1

A bag contains 5 red marbles, 3 blue marbles, and 2 green marbles. If you randomly select one marble, what is the probability of selecting a blue marble?

Solution:

  1. Total marbles: n(S) = 5 + 3 + 2 = 10
  2. Blue marbles: n(blue) = 3
  3. P(blue) = 3/10 = 0.3

Answer: 3/10 or 0.3 or 30%

Practice Question 2

What is the probability of rolling a number less than or equal to 4 on a fair six-sided die?

Solution:

  1. Sample space: S = {1, 2, 3, 4, 5, 6}, n(S) = 6
  2. Event A = "rolling ≤ 4" = {1, 2, 3, 4}, n(A) = 4
  3. P(A) = 4/6 = 2/3 ≈ 0.667

Answer: 2/3 or about 66.7%

Practice Question 3

If P(A) = 0.42, what is P(not A)?

Solution:

Using the complement rule:

P(not A) = 1 − P(A) = 1 − 0.42 = 0.58

Answer: 0.58 or 58%

Practice Question 4

When rolling two six-sided dice, how many outcomes are in the sample space?

Solution:

Each die has 6 possible outcomes.

First die: 6 outcomes

Second die: 6 outcomes

Total outcomes = 6 × 6 = 36

(We'll learn more about this multiplication principle in Lesson 2!)

Answer: 36 outcomes

Practice Question 5

True or False: A probability of 1.25 is possible.

Answer: FALSE

Explanation:

All probabilities must be between 0 and 1 (inclusive).

A probability of 1.25 is greater than 1, which violates the fundamental rule that 0 ≤ P(A) ≤ 1.

If you calculate a probability greater than 1, you've made an error!

Key Takeaways

  • Probability measures likelihood with a number between 0 and 1
  • Sample space (S) contains all possible outcomes
  • Event (A) is a collection of outcomes we're interested in
  • Classical formula: P(A) = n(A) / n(S) (when outcomes equally likely)
  • Range rule: 0 ≤ P(A) ≤ 1 always
  • Complement rule: P(not A) = 1 − P(A)
  • Certain event: P(S) = 1
  • Impossible event: P(∅) = 0

What's Next?

You've learned the fundamentals of probability! In Lesson 2: Counting Methods, you'll master techniques for systematically counting outcomes—essential for more complex probability problems.

Coming up: Fundamental Counting Principle, Permutations, and Combinations

← Module Home ← Pre-Assessment Next: Counting Methods →