Definition and Examples of a Sample Space in Statistics

Close-Up Of Hand Holding Coin

The collection of all possible outcomes of a probability experiment forms a set that is known as the sample space.

Probability concerns itself with random phenomena or probability experiments. These experiments are all different in nature and can concern things as diverse as rolling dice or flipping coins. The common thread that runs throughout these probability experiments is that there are observable outcomes. The outcome occurs randomly and is unknown prior to conducting our experiment.

In this set theory formulation of probability, the sample space for a problem corresponds to an important set. Since the sample space contains every outcome that is possible, it forms a set of everything that we can consider. So the sample space becomes the universal set in use for a particular probability experiment.

Common Sample Spaces

Sample spaces abound and are infinite in number. But there are a few that are frequently used for examples in an introductory statistics or probability course. Below are the experiments and their corresponding sample spaces:

Forming Other Sample Spaces

The above list includes some of the most commonly used sample spaces. Others are out there for different experiments. It is also possible to combine several of the above experiments. When this is done, we end up with a sample space that is the Cartesian product of our individual sample spaces. We can also use a tree diagram to form these sample spaces.

For example, we may want to analyze a probability experiment in which we first flip a coin and then roll a die. Since there are two outcomes for flipping a coin and six outcomes for rolling a die, there are a total of 2 x 6 = 12 outcomes in the sample space we are considering.