What is a sample space in probability?

The concept of a sample space is fundamental in probability theory, as it provides the foundation for understanding how probabilities are assigned to outcomes. The sample space is defined as the complete set of all possible outcomes that can occur in a particular experiment or random trial.

For example, if you were to flip a coin, the sample space includes two outcomes: heads and tails. If you rolled a six-sided die, the sample space would consist of the outcomes 1, 2, 3, 4, 5, and 6. By identifying the entire sample space, you can analyze probability calculations, such as finding the likelihood of a specific event occurring within that space.

Regarding the other options, while the average of experimental outcomes pertains to statistical measures, it does not define what a sample space is. A selection of outcomes based on criteria refers to a subset of the sample space and not the entire set itself. Similarly, a single outcome from an experiment represents an individual result within the sample space, rather than the complete set of potential outcomes. Therefore, the definition of a sample space as a set containing all possible outcomes is the most accurate and relevant answer.