Which statement best describes experimental probability?

Experimental probability is defined as the ratio of the number of successful outcomes to the total number of trials conducted. This concept is rooted in empirical observation, where a probability is calculated based on the results of actual experiments or practical trials rather than theoretical outcomes.

In practice, if you were to conduct an experiment, say flipping a coin 100 times, and you observed that it landed on heads 55 times, the experimental probability of getting heads would be 55 divided by 100. This demonstrates that experimental probability is based on real-world results and thus can vary with each set of trials.

The other responses do not accurately capture the essence of experimental probability. Theoretical outcomes divided by actual outcomes, for example, would instead pertain to theoretical probability, which is calculated based on expected outcomes rather than actual results. The total possible outcomes describe the sample space of an event and would not yield the probability without considering the number of successful outcomes. Finally, the average outcome of a series of events does not necessarily reflect probability but rather a mean value, which is a distinct concept from calculating experimental probability.