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First teaching 2023

First exams 2025

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Basic Probability (CIE IGCSE Maths: Core)

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Basic Probability

What is probability?

  • Probability describes the likelihood of something happening
    • In real-life you might use words such as impossible, unlikely and certain
  • In maths we use the probability scale to describe probability
    • This means giving it a number between 0 and 1
      • 0 means impossible
      • Between 0 and 0.5 means unlikely
      • 0.5 means even chance
      • Between 0.5 and 1 means likely
      • 1 means certain
  • Probabilities can be given as fractions, decimals or percentages

What key words and terminology are used in probability?

  • An experiment is an activity that is repeated to produce a set of results
    • Results can be observed (seen) or recorded
    • Each repeat is called a trial
  • An outcome is a possible result of a trial
  • An event is an outcome (or a collection of outcomes)
    • For example:
      • a dice lands on a six
      • a dice lands on an even number
    • Events are usually given capital letters
    • n(A) is the number of possible outcomes from event A
      • A = a dice lands on an even number (2, 4 or 6)
      • n(A) = 3 
  • A sample space is the set of all possible outcomes of an experiment
    • It can be represented as a list or a table
  • The probability of event A is written P(A)
  • An event is said to be fair if there is an equal chance of achieving each outcome
    • If there is not an equal chance, the event is biased
    • For example, a fair coin has an equal chance of landing on heads or tails

How do I calculate basic probabilities?

  • If all outcomes are equally likely then the probability for each outcome is the same
    • The probability for each outcome is fraction numerator 1 over denominator Total space number space of space outcomes end fraction
      • If there are 50 marbles in a bag then the probability of selecting a specific one is 1 over 50
  • The theoretical probability of an event can be calculated by dividing the number of outcomes of that event by the total number of outcomes
    • straight P left parenthesis A right parenthesis equals fraction numerator Total space number space of space outcomes space for space the space event over denominator Total space number space of space outcomes end fraction 
    • This can be calculated without actually doing the experiment 
      • If there are 50 marbles in a bag and 20 are blue, then the probability of selecting a blue marble is 20 over 50

How do I find missing probabilities?

  • The probabilities of all the outcomes add up to 1
    • If you have a table of probabilities with one missing, find it by making them all add up to 1 
  • The complement of event A is the event where A does not happen
    • This can be thought of as not A
    • P(event does not happen) = 1 - P(event does happen)
      • For example, if the probability of rain is 0.3, then the probability of not rain is 1 - 0.3 = 0.7

What are mutually exclusive events?

  • Two events are mutually exclusive if they can not both happen at once
    • When rolling a dice, the events “getting a prime number” and “getting a 6” are mutually exclusive
  • If A and B are mutually exclusive events, then the probability of either A or B happening is P(A) + P(B)
  • Complementary events are mutually exclusive

Exam Tip

  • If you are not told in the question how to leave your answer, then fractions are best for probabilities.

Worked example

Emilia is using a spinner that has outcomes and probabilities as shown in the table.

Outcome Blue Yellow Green Red Purple
Probability   0.2 0.1   0.4


The spinner has an equal chance of landing on blue or red.

(a)

Complete the probability table.

The probabilities of all the outcomes should add up to 1

1 - 0.2 - 0.1 - 0.4 = 0.3

The probability that it lands on blue or red is 0.3
As the probabilities of blue and red are equal you can halve this to get each probability

0.3 ÷ 2 = 0.15

Now complete the table

Outcome Blue Yellow Green Red Purple
Probability 0.15 0.2 0.1 0.15 0.4


  

(b)

Find the probability that the spinner lands on green or purple.

As the spinner cannot land on green and purple at the same time they are mutually exclusive
This means you can add their probabilities together

0.1 + 0.4 = 0.5

P(Green or Purple) = 0.5

 

c)

Find the probability that the spinner does not land on yellow.

The probability of not landing on yellow is equal to 1 minus the probability of landing on yellow

1 - 0.2 = 0.8

P(Not Yellow) = 0.8

Possibility Diagrams

What is a possibility diagram?

  • In probability, the sample space means all the possible outcomes
  • In simple situations it can be given as a list
    • For flipping a coin, the sample space is: Heads, Tails
      • the letters H, T can be used
    • For rolling a six-sided dice, the sample space is:  1, 2, 3, 4, 5, 6 
  • If there are two sets of outcomes, a grid can be used
    • These are called possibility diagrams (or sample space diagrams)
    • For example, roll two six-sided dice and add their scores
    • A list of all the possibilities would be very long
      • You might miss a possibility
      • It would be hard to spot any patterns in the sample space

Possibility diagram for the sum of scores of two dice

  • Combining more than two sets of outcomes must be done by listing the possibilities
    • For example, flipping three coins
      • The sample space is HHH, HHT, HTH, THH, HTT, THT, TTH, TTT (8 possible outcomes)

How do I use a possibility diagram to calculate probabilities?

  • Probabilities can be found by counting the number of possibilities you want, then dividing by the total number of possibilities in the sample space
    • In the sample space 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, there are four prime numbers (2, 3, 5 and 7)
      • The probability of getting a prime number is  4 over 10 equals 2 over 5
    • Using the possibility diagram above for rolling two dice, the probability of getting an eight is  5 over 36
      • There are 5 eights in the grid, out of the total 36 numbers
  • Be careful, this counting method only works if all possibilities in the sample space are equally likely
    • For a fair six-sided dice: 1, 2, 3, 4, 5, 6 are all equally likely
    • For a fair (unbiased) coin: H, T are equally likely
    • Winning the lottery: Win, Lose are are not equally likely! 
      • You cannot count possibilities here to say the probability of winning the lottery is  1 half 

Exam Tip

  • Some harder questions may not say "by drawing a possibility diagram" so you may have to do it on your own.

Worked example

Two fair six-sided dice are rolled.

(a)
Find the probability that the sum of the numbers showing on the two dice is an odd number greater than 5, giving your answer as a fraction in simplest form.

Draw a possibility diagram to show all the possible outcomes

Possibility diagram for the sum of scores of two dice

Circle the possibilities that are odd numbers greater than 5
(5 is not included)

Possibility diagram for the sum of scores of two dice with the odd values greater than 5 circled

Count the number of possibilities that are circled (12) and divide them by the total number of possibilities in the diagram (36)

12 over 36
Cancel the fraction

12 over 36 space equals space fraction numerator 12 cross times 1 over denominator 12 cross times 3 end fraction space equals space 1 third
bold 1 over bold 3

(b)
Given that the sum of the numbers showing on the two dice is an odd number greater than 5, find the probability that one of the dice shows the number 2. Give your answer as a fraction in simplest form.

From part (a) you already know there are 12 ways to get an odd number greater than 5
Out of these 12 possibilities, only two possibilities had the number 2 on a dice: (2, 5) and (5, 2)
So the probability we are looking for is 2 divided by 12

2 over 12
Cancel the fraction

2 over 12 space equals space fraction numerator 2 cross times 1 over denominator 2 cross times 6 end fraction space equals space 1 over 6
bold 1 over bold 6

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Mark

Author: Mark

Mark graduated twice from the University of Oxford: once in 2009 with a First in Mathematics, then again in 2013 with a PhD (DPhil) in Mathematics. He has had nine successful years as a secondary school teacher, specialising in A-Level Further Maths and running extension classes for Oxbridge Maths applicants. Alongside his teaching, he has written five internal textbooks, introduced new spiralling school curriculums and trained other Maths teachers through outreach programmes.