MathBored

Essential Math Primer
← Back to Primer Overview
G08 • Lesson 49 of 105

Probability: Sample Spaces & Experimental vs Theoretical

Introduces probability as a measure from 0 to 1 representing likelihood. Students list sample spaces for simple and compound events, calculate theoretical probability using equally likely outcomes, conduct experiments to find experimental (relative frequency) probability, and compare the two as trial counts increase (law of large numbers intuition).

Middle School Geometry & Data • 6-8

Prerequisites: E12

Key Concepts

  • probability scale from 0 (impossible) to 1 (certain)
  • sample spaces for simple and compound events
  • theoretical probability as favorable outcomes over total outcomes
  • experimental probability and the law of large numbers

Probability: Sample Spaces & Experimental vs. Theoretical

Probability measures how likely an event is to happen. It is a number between 0 (impossible) and 1 (certain). Understanding probability helps you make predictions, evaluate risk, and think critically about chance in games, science, and everyday decisions.

The Probability Scale

0 ———— 0.25 ———— 0.5 ———— 0.75 ———— 1
Impossible    Unlikely    Equally Likely    Likely    Certain

Probability can be written as a fraction, decimal, or percent. For example, 1/4 = 0.25 = 25%.

Sample Spaces

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

Simple Events:

  • Coin flip: {Heads, Tails} — 2 outcomes
  • Standard die: {1, 2, 3, 4, 5, 6} — 6 outcomes

Compound Events:

  • Two coin flips: {HH, HT, TH, TT} — 4 outcomes
  • Die + coin: 6 × 2 = 12 outcomes

For compound events, multiply the number of outcomes in each individual experiment (this is the counting principle).

Theoretical Probability

P(event) = Number of favorable outcomes / Total number of outcomes

This formula works when all outcomes are equally likely. You calculate it by reasoning, without running an experiment.

Experimental Probability

P(event) = Number of times event occurred / Total number of trials

This is based on actual data from performing the experiment. It may differ from the theoretical probability, especially with few trials.

Law of Large Numbers

As you perform more and more trials, the experimental probability gets closer and closer to the theoretical probability. Flip a coin 10 times and you might get 70% heads. Flip it 10,000 times and you will get very close to 50%. This pattern is called the Law of Large Numbers.

Example 1 — Theoretical Probability with a Die

What is the probability of rolling a number greater than 4 on a standard die?

  • Sample space: {1, 2, 3, 4, 5, 6} — 6 outcomes.
  • Favorable outcomes (greater than 4): {5, 6} — 2 outcomes.
  • P = 2/6 = 1/3 ≈ 0.333 ≈ 33.3%.
  • Example 2 — Compound Sample Space

    You flip a coin and roll a die. What is the probability of getting Heads and a 3?

  • Total outcomes: 2 × 6 = 12.
  • Favorable outcome: {H, 3} — 1 outcome.
  • P = 1/12 ≈ 0.083 ≈ 8.3%.
  • Example 3 — Experimental vs. Theoretical

    A spinner has 4 equal sections: red, blue, green, yellow. You spin 50 times and get red 16 times. Compare experimental and theoretical probability of red.

  • Theoretical: P(red) = 1/4 = 0.25 = 25%.
  • Experimental: P(red) = 16/50 = 0.32 = 32%.
  • The experimental probability (32%) is higher than theoretical (25%). With more spins, it would likely move closer to 25% (Law of Large Numbers).
  • Listing Compound Outcomes

    For compound events, use an organized list, a tree diagram, or a table to avoid missing outcomes. For two coins: list HH, HT, TH, TT. Note that HT and TH are different outcomes (first coin vs. second coin), so do not combine them.

    Common Mistake

    Students sometimes think that after flipping 5 heads in a row, tails is "due." Each flip is independent—past results do not change future probabilities. The coin has no memory. P(Tails) is always 1/2 on any single flip.

    Practice Problems

    1. A bag holds 3 red, 5 blue, and 2 green marbles. What is the probability of drawing a blue marble?

    Show Solution

    Total = 3 + 5 + 2 = 10. P(blue) = 5/10 = 1/2 = 50%.

    2. List the sample space for flipping three coins. How many outcomes are there?

    Show Solution

    {HHH, HHT, HTH, HTT, THH, THT, TTH, TTT} — 8 outcomes (2 × 2 × 2 = 8).

    3. Using the sample space from Problem 2, what is P(exactly 2 heads)?

    Show Solution

    Favorable: {HHT, HTH, THH} = 3 outcomes. P = 3/8 = 0.375 = 37.5%.

    4. A student rolls a die 60 times and gets a 6 exactly 8 times. (a) What is the experimental probability? (b) What is the theoretical probability? (c) Are they close?

    Show Solution

    (a) Experimental: 8/60 = 2/15 ≈ 13.3%. (b) Theoretical: 1/6 ≈ 16.7%. (c) Reasonably close; with more trials the experimental probability would likely approach 16.7%.

    5. An event has probability 0. What does this mean? What about probability 1?

    Show Solution

    Probability 0 means the event is impossible—it cannot happen. Probability 1 means the event is certain—it must happen. All probabilities fall between these extremes.

    Lesson Summary

    Overview