Year 7 Mathematics | Victorian Curriculum 2.0
Probability
Topic 15 | Statistics & Probability | Practice

What you will learn

  • use the probability scale from 000 (impossible) to 111 (certain),
  • list the sample space of a simple experiment and count outcomes,
  • calculate theoretical probability for equally likely outcomes,
  • understand complementary events and use P(A′)=1−P(A)P(A') = 1 - P(A)P(A′)=1−P(A),
  • compare experimental and theoretical probability.
Why measure chance with numbers?

Words like “unlikely” or “probably” mean different things to different people. Probability replaces vague language with a number between 000 and 111: 000 means impossible, 111 means certain, and everything else sits between. This scale is universal — a probability of 0.30.30.3 means the same thing whether you are talking about rain, dice, or medical tests. Numbers make comparisons precise.

Where you'll see this
  • Weather: “70% chance of rain tomorrow” is a probability.
  • Games: board games, card games, lotteries — all use probability.
  • Insurance: premiums are calculated from the probability of a claim.
  • Medicine: a treatment’s success rate is reported as a probability.
Worked example 0 Real-world example: should you take an umbrella?

The forecast says “70% chance of rain.” What does that actually mean, and should you carry an umbrella?

  1. 70%=0.770\% = 0.770%=0.7 — on the probability scale, that is well above “even chance” (0.50.50.5).
  2. The complement: P(no rain)=1−0.7=0.3P(\text{no rain}) = 1 - 0.7 = 0.3P(no rain)=1−0.7=0.3 — only a 30%30\%30% chance of staying dry.
  3. If you skip the umbrella, roughly 777 out of 101010 times you’d get wet.
  4. Decision: take the umbrella.

Key idea: probability turns a vague “it might rain” into a precise number you can compare and act on.

1. The probability scale

Every probability is a number between 000 and 111 inclusive. It can be written as a fraction, a decimal, or a percentage.

0Impossible0.25Unlikely0.5Even chance0.75Likely1CertainP(6 on die)P(rain 70%)
The probability scale from 0 (impossible) to 1 (certain). Common benchmarks are shown along the line.

2. Sample space and equally likely outcomes

The sample space is the list of all possible outcomes of an experiment. An experiment has equally likely outcomes if each one has the same chance of occurring.

Theoretical probability

For equally likely outcomes
P(A)  =  number of outcomes in Atotal number of outcomes.P(A) \;=\; \frac{\text{number of outcomes in } A}{\text{total number of outcomes}}.P(A)=total number of outcomesnumber of outcomes in A​.
123456
Sample space for a fair six-sided die. All 6 outcomes are equally likely. The 3 shaded outcomes (even numbers) give P(even) = 3/6 = 1/2.
Worked example 1 Rolling a fair die

A fair six-sided die is rolled. What is the probability of rolling:

(a) a 444? There is one favourable outcome out of six:

P(4)=16.P(4) = \frac{1}{6}.P(4)=61​.

(b) an even number? Favourable outcomes: 2,4,62, 4, 62,4,6, so

P(even)=36=12.P(\text{even}) = \frac{3}{6} = \frac{1}{2}.P(even)=63​=21​.

(c) a number greater than 666? No outcomes satisfy this, so

P(>6)=0.P(>6) = 0.P(>6)=0.

3. Complementary events

The complement of event AAA (written A′A'A′) is “not AAA”.

Complement rule
P(A)+P(A′)  =  1,soP(A′)=1−P(A).P(A) + P(A') \;=\; 1, \qquad \text{so} \qquad P(A') = 1 - P(A).P(A)+P(A′)=1,soP(A′)=1−P(A).
Worked example 2 Using the complement

A bag has 333 red, 555 blue, 222 green marbles. A marble is drawn at random.

P(red)=310,P(not red)=1−310=710.P(\text{red}) = \frac{3}{10}, \qquad P(\text{not red}) = 1 - \frac{3}{10} = \frac{7}{10}.P(red)=103​,P(not red)=1−103​=107​.

4. Experimental probability

The experimental probability of an event is its observed frequency in a trial:

Experimental probability
Pexp(A)  =  number of trials where A occurredtotal number of trials.P_{\mathrm{exp}}(A) \;=\; \frac{\text{number of trials where } A \text{ occurred}}{\text{total number of trials}}.Pexp​(A)=total number of trialsnumber of trials where A occurred​.
The Law of Large Numbers

As the number of trials grows, experimental probability tends to approach the theoretical probability.

Worked example 3 Coin toss experiment

A coin is flipped 200200200 times. Heads comes up 949494 times.

Experimental P(heads)=94200=0.47P(heads) = \dfrac{94}{200} = 0.47P(heads)=20094​=0.47.

This is close to the theoretical probability of 0.50.50.5 for a fair coin, but not exactly equal - short-run randomness means exactly half is not guaranteed.


Practice

Fluency

Tier 1: basic skills

    A fair six-sided die is rolled for questions 1-5.

    1. P(rollinga3)P(rolling a 3)P(rollinga3).
    2. P(odd)P(odd)P(odd).
    3. P(numberlessthan3)P(number less than 3)P(numberlessthan3).
    4. P(numbergreaterthan4)P(number greater than 4)P(numbergreaterthan4).
    5. P(rollinga7)P(rolling a 7)P(rollinga7).

    A bag has 444 red, 333 blue, 222 green, 111 yellow marble (101010 total). For questions 6-10:

    1. P(red)P(red)P(red).

    2. P(blue)P(blue)P(blue).

    3. P(notgreen)P(not green)P(notgreen).

    4. P(redorblue)P(red or blue)P(redorblue).

    5. P(pink)P(pink)P(pink).

    6. What is P(certain)P(certain)P(certain)?

    7. What is P(impossible)P(impossible)P(impossible)?

    8. Convert probability 0.40.40.4 to a fraction and to a percentage.

    9. P(A)=38P(A) = \dfrac{3}{8}P(A)=83​. Find P(A′)P(A')P(A′).

    10. A fair coin is flipped. What is P(heads)P(heads)P(heads)?

    11. A spinner has sectors coloured red/red/blue/green/green/green. Find P(green)P(green)P(green).

Reasoning

Tier 2: mixed practice

    1. A bag contains 555 red and 777 blue counters. A counter is drawn at random. Find P(red)P(red)P(red) and P(blue)P(blue)P(blue).
    2. A coin is flipped twice. List the sample space.
    3. A spinner has four equal sectors labelled 1,2,3,41, 2, 3, 41,2,3,4 and is spun twice. How many outcomes are in the sample space?
    4. Two dice are rolled and the sum is recorded. What is the most likely sum? What is its probability?
    5. A bag has 121212 marbles: xxx red and the rest blue. If P(red)=14P(red) = \dfrac{1}{4}P(red)=41​, how many red marbles are there?
    6. A card is drawn from a standard deck of 525252. Find P(heart)P(heart)P(heart).
    7. A card is drawn from a standard deck. Find P(facecard)P(face card)P(facecard). (Face cards are J, Q, K; 121212 in total.)
    8. If P(A)=0.35P(A) = 0.35P(A)=0.35, what is P(A′)P(A')P(A′)?
Reasoning

Tier 3: explain and spot the mistake

    1. A student says “I flipped a coin 444 times and got 333 heads, so the probability of heads is 34\dfrac{3}{4}43​”. Explain what is right and what is wrong in this statement.
    2. After flipping a coin and getting tails 555 times in a row, Ben says “the next flip is more likely to be heads”. Is Ben correct? Explain.
    3. Leah says “the probability of rain tomorrow is 110%110\%110%”. Explain why this cannot be right.
    4. Give an example of two events where P(A)+P(B)=1P(A) + P(B) = 1P(A)+P(B)=1 but AAA and BBB are not complements.
Problem solving

Tier 4: real-world problems

    1. A weather report gives the chance of rain tomorrow as 30%30\%30%. What is the probability it does not rain?
    2. A class has 282828 students: 121212 play netball, 161616 do not. One student is chosen at random. Find the probability the student plays netball.
    3. In a raffle with 500500500 tickets, you buy 202020. What is the probability you win? Express as a percentage and as a decimal.
    4. A fair die is rolled 606060 times. How many times would you expect to roll a 666? If actually 141414 sixes came up, what is the experimental probability?
    5. A spinner is divided into sectors of sizes 1,2,3,41, 2, 3, 41,2,3,4 (measured in equal angle units summing to 101010). Find the probability of landing on the largest sector.
    6. A bag has 888 red, 555 blue and some green marbles. If P(green)=14P(green) = \dfrac{1}{4}P(green)=41​, how many green marbles are in the bag?
Year 7 Mathematics study companion | Practice