An **event space** contains all possible events for a given experiment or happening. An *event *is just a **set of outcomes** of an experiment, combined with their probability. And an “*experiment*” has a meaning a little different to the one we use in ordinary speech: it’s anything, with a well-defined set of possible outcomes, that can be repeated infinitely.

## Examples of Event Space

An event space is often denoted by the Greek letter sigma (Σ). It’s sometimes confused with the sample space of an experiment, referred to usually by omega(Ω), but is different: while the sample space of an experiment contains all possible outcomes, the event space contains all *sets of outcomes*; all subsets of the sample space.

## Example 1: Coin Flip

For a simple coin flip, the two possible outcomes are either heads or tails, so the **sample space **is given by

Ω = {H, T}

The **event space** is a little different. The possible events are:

- {H}—rolling the die and getting heads,
- {T}—rolling the die and getting tails,
- {H,T}—rolling the die and getting either heads
*or*tails.

Because each of these are different subsets of the sample space, they count as different events, even though {H} (heads) would imply {H, T} (either H or T). The event space contains all three of those events:

Σ= {(H), (T), (H,T)}

## Example 2: Coin Flip

For the roll of a die, the **sample space** is {1, 2, 3, 4, 5, 6}.

One event, if you roll the die three times, is {2,4,6}

(In English, we’d call this ‘the roll of the dice is even’)

Another event could be {1,2}

(We could call this ‘getting less than 3’)

The collection of every possible set (there are an infinite amount, depending on how many times you choose to roll that die) of those six numbers form the event space Σ.

## Sources

Kirkpatrick, K. Sample Space, Events, and Probability

Retrieved from https://faculty.math.illinois.edu/~kkirkpat/SampleSpace.pdf on April 16, 2018.

Probability Methods in Civil Engineering. Lecture 6: Introduction to probability: Sample space, event space and events

Retrieved from http://nptel.ac.in/courses/105103027/6 on April 16, 2018

Garrett, Paul. Basic Probability. Retrieved from http://www-users.math.umn.edu/~garrett/crypto/Overheads/03_prob.pdf on April 16, 2018

------------------------------------------------------------------------------**Need help with a homework or test question?** With Chegg Study, you can get step-by-step solutions to your questions from an expert in the field. If you'd rather get 1:1 study help, Chegg Tutors offers 30 minutes of **free tutoring** to new users, so you can try them out before committing to a subscription.

If you prefer an **online interactive environment** to learn R and statistics, this *free R Tutorial by Datacamp* is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try *this Statistics with R track*.

**Comments? Need to post a correction?** Please post a comment on our *Facebook page*.

Check out our updated Privacy policy and Cookie Policy