Probability foundations · Definition

Event

probabilityfoundations

Before you start you need to know

Probability questions are rarely about a single outcome but about situations like «an even number shows»; events represent them.

Definition

An event \(A\) is a subset of the sample space \(\Omega\): the set of outcomes for which a given condition holds.

\[A\subseteq\Omega\]

We say an event \(A\) occurs when the outcome of the experiment belongs to \(A\). On a die, «an even number shows» is \(A=\{2,4,6\}\). An event with a single outcome is called elementary; \(\Omega\) is the sure event and \(\varnothing\) the impossible one.

Since events are sets, they combine through set operations: the union \(A\cup B\) is «\(A\) or \(B\) occurs», the intersection \(A\cap B\) is «both occur» and the complement \(A^c\) is «\(A\) does not occur». With \(A=\{2,4,6\}\) and \(B=\{4,5,6\}\) we get \(A\cap B=\{4,6\}\) and \(A\cup B=\{2,4,5,6\}\). If \(A\cap B=\varnothing\), the events are mutually exclusive.

If \(\Omega\) has \(n\) elements, there are \(2^n\) possible events, because each outcome is either in the subset or not. That is why, in large spaces, it is better to describe events by a condition than to list their elements.

A frequent mistake is to call a single outcome an «event» or to confuse «mutually exclusive» with «independent»; these are different ideas, and we will meet them later. Assigning a number to each event is the topic of the next concept.

Think about it

Can an event be both elementary and impossible?

No. An elementary event contains exactly one outcome, while the impossible event is the empty set.

Exercises 10

References

  • Joseph K. Blitzstein, Jessica Hwang, Introduction to Probability, 2nd edition, CRC Press, 2019. §1.2
  • Sheldon Ross, A First Course in Probability, 10th edition, Pearson, 2019. §2.3
  • Larry Wasserman, All of Statistics, 1st edition, Springer, 2004. §2.2