Probability Symbol

Here we will learn about probability symbols, including union, intersection and complement notation.

There are also probability symbols worksheets based on Edexcel, AQA and OCR exam questions, along with further guidance on where to go next if you’re still stuck.

What are probability symbols?

Probability symbols are the symbols we might see in a GCSE question involving set notation and Venn diagrams.

To use probability symbols along with others to write mathematical statements, we need to understand what each symbol represents.

For example, below is a Venn diagram (a joint probability distribution) showing the following information,

• \xi = \{1,2,3,4,5,6,7,8,9,10\}
• A = \{ even numbers \}
• B = \{ multiples of 3\}

The probability of an even number that is also a multiple of 3 in the Venn diagram above is \frac{1}{10}. This is because there is only 1 value (or element) in the intersection of the Venn diagram, out of a total of 10 values (or elements).

Step-by-step guide: Venn diagrams

In probability theory, probability symbols allow the reader to shorten a mathematical statement so that it is more clear and concise.

If we used probability symbols to represent the previous probability in the Venn diagram above (the probability of selecting an even number and a multiple of 3 ), we would write P(A\cap{B})=\frac{1}{10}. This also reads as the probability of A intersection B is equal to one tenth.

The table below outlines key set notation that is used within probability theory; the next table outlines key probability symbols alongside their description.

We can use these symbols for probability purposes.

Here is what each symbol means in the context of probability.

Note: P(x) is the probability of the random variable x occurring. The P is a capital letter.

What are probability symbols?

How to answer questions with probability symbols

In order to answer questions with probability symbols:

1. Identify the probability description from the symbols being used.
2. Identify the frequency of the event required.
3. Divide the frequency of the event by the total number of outcomes.

Explain how to answer questions with probability symbols

Related lessons on describing probability

Probability symbol is part of our series of lessons to support revision on describing probability. You may find it helpful to start with the main describing probability lesson for a summary of what to expect, or use the step by step guides below for further detail on individual topics. Other lessons in this series include:

• Describing probability
• Probability scale
• Probability notation

Probability symbol examples

Example 1: calculating the probability of event A happening

Let \xi = \{1,2,3,4,5,6,7,8,9,10\} and A = \{ prime number \}. A number is selected at random from \xi. Calculate P(A).

1. Identify the probability description of the symbols being used.

As A = \{ prime number \}, the set of A contains the items 2, 3, 5, and 7. This is written as A= \{2,3,5,7\}.

2Identify the frequency of the event required.

There are four numbers in the set of A and so A has a frequency of 4.

3Divide the frequency of the event by the total number of outcomes.

There are 10 numbers in the universal set, \xi. Therefore,

Example 2: calculating the probability of event A not happening

Let \xi = \{1,2,3,4,5,6,7,8,9,10,11,12,13,14,15\} and A = \{ multiple of 4\}. A number is selected at random. Calculate P(A’)

Example 3: calculating the probability of event A and B happening

Let \xi = \{1,2,3,4,5,6,7,8,9,10\}, \ A = \{ prime number \} and B = \{ even number\}. Determine the value of P(A\cap{B}). Express your solution as a decimal.

Example 4: calculating the probability of event A or B happening

The Venn diagram shows the frequency of 40 students who study two subjects,

F=\{ Students studying French \}, and S=\{ Students studying Spanish \}.

Calculate P(F\cup{S}).

Identify the probability description of the symbols being used.

Given that F = \{ Students studying French \} and S = \{ Students studying Spanish \} where \cup represents the union of two sets, we have F\cup{S} = \{ Students studying French or Spanish \}.

Example 5: calculating the probability of event A happening and B not happening

The Venn diagram shows information about two sets A and B.

Calculate P(A\cap{B}’).

Identify the probability description of the symbols being used.

A\cap{B’} = \{ elements in set A but not set B\}.

Example 6: calculating the probability of event B not happening or C happening

65 students were asked whether they liked B=\{ Banana} and C=\{ Custard \}. The results are represented in the Venn diagram below.

Calculate the probability P(B’\cup{C}).

Identify the probability description of the symbols being used.

The symbols B’\cup{C} is the set of elements not in set B, or the elements in set C. Contextually, we want to calculate the probability that a student likes banana and custard, custard only, or neither.

Common misconceptions

• Confusing the intersection symbol with the union symbol

The two symbols ∪ and ∩ have two different meanings. The intersection of two sets means that the item is in both of these sets, whereas the union of two sets, the item can be in one or the other, or both.

It is common for students to forget that elements in the union (U) of two sets can be excluded from the description of one of the sets in the union.

The next lessons are

• Probability distribution
• How to calculate probability
• Combined events probability

Beyond GCSE

The study of probability theory and statistics is covered much more in depth at A level. This is because there are certain situations where the probability of an event cannot be given and so we have to define a probability from a range.

This in turn means that there are an increasing number of probability and statistics symbols covered, including the use of greek letters.

Probability theory studies at A level include,

• Probability distributions including their geometric distribution,
  ◌ The normal distribution
  ◌ The binomial distribution
  ◌ The poisson distribution
• Probability density functions
• Cumulative distribution functions (cdf)
• Correlation (corr) and regression
• Sample standard deviation (std), variance and covariance (cov)
• Degrees of freedom
• Factorials
• Permutations
• Probability mass function (pmf)
• Population mean and sample mean
• Set theory
• Summation

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