Grade 7 · Grade 7: Sampling and Probability · Sampling and Probability

Probability Models and Compound Events

Statistics & ProbabilityCore50 min

Move between theoretical and experimental probability, then count compound outcomes with lists, tables and tree diagrams.

Learning objectives

  • Place probabilities on a 0 to 1 scale.
  • Compare experimental relative frequency with theoretical probability.
  • List sample spaces for compound events.
  • Use simulation to estimate probabilities.

AERO Mathematics alignment

  • AERO.M7.SP.4

    Understand that the probability of a chance event is a number between 0 and 1 that expresses its likelihood.

  • AERO.M7.SP.5

    Approximate the probability of a chance event by collecting data, and compare experimental results with a theoretical probability model.

  • AERO.M7.SP.6

    Find probabilities of compound events using organised lists, tables, tree diagrams and simulation.

MYP criteria

  • Criterion AKnowing and understanding
  • Criterion BInvestigating patterns
  • Criterion CCommunicating
  • Criterion DApplying mathematics in real-life contexts

ENGAGE

Start here

You toss a fair coin nine times and get heads every time.

Think about it

What is the probability the tenth toss is heads?

Hint: Does the coin remember what it did before?

EXPLAIN

From theory to experiment

The probability of an event is a number from 0 (impossible) to 1 (certain). Theoretical probability uses the structure of the situation: a fair die gives P(4) = 1/6. Experimental probability uses data: relative frequency = successes ÷ trials.

TrialsHeadsRelative frequency
1070.70
100540.54
10005080.508

As the number of trials grows, the relative frequency settles near the theoretical value. This is the law of large numbers, and it says nothing at all about the next single trial.

Compound events

For two coins, the sample space is HH, HT, TH, TT, so P(exactly one head) = 2/4 = 0.5. Organised lists, tables and tree diagrams make sure no outcome is missed.

Common misconception

There is no law of averages for a fair coin. After nine heads, the probability of heads next is still exactly 0.5, because tosses are independent.

INVESTIGATION

Try it yourself

Roll two dice 50 times and record the sums. Compare your experimental probabilities with the theoretical ones from a 6 × 6 table. Which sum was furthest from theory, and what would you expect after 500 rolls?

Watch

Basic Probability

Math Antics · 11:28

Connects theoretical probability with what actually happens when you experiment.

Before you watch: Can a probability be 1.4?

  1. Estimate P(heads) after 500 tosses. How close is it to 0.5?
  2. List the sample space for tossing two coins.
Open on YouTube

Interactive simulation · PhET

Plinko Probability

Compare the experimental distribution with the theoretical one as the number of trials grows.

While you explore

  1. How close is the experimental probability to the theoretical value after 1000 trials?
  2. What does this tell you about a single trial?
Open full screen on PhET

Key vocabulary

Relative frequency
How often something actually happened, as a fraction of trials.
Sample space
A list of everything that could happen.

Practice questions

0/1 correct

Level 1 · Criterion A

A fair six-sided die is rolled. What is P(rolling a number greater than 4)?

MYP criterion tasks

Level 2 · Criterion B

Two coins are tossed. List the sample space and find P(at least one head).

Reflect & track

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