Which aspect does experimental probability rely on?

Experimental probability is fundamentally based on the observable results obtained from conducting experiments or trials. This type of probability is determined by performing an experiment a certain number of times and recording the outcomes, which then allows us to calculate the probability of an event occurring based on the frequency of its occurrence in those trials.

By focusing on actual results rather than theoretical models or calculations derived from historical data, experimental probability provides a practical approach to understanding likelihood in real-world situations. This reliance on real data helps in situations where theoretical predictions may not accurately reflect outcomes. For example, if you're determining the probability of rolling a certain number on a die, the experimental probability would be derived from rolling the die multiple times and noting how often the desired number appears relative to the total rolls.

In contrast, other choices such as theoretical predictions and past event calculations do not align with the core principle of experimental probability, since they do not stem from actual observed outcomes but rather from assumptions or historical data. Additionally, focusing solely on the rate of failure in trials does not encompass the broader context of measuring all possible outcomes and probabilities that experimental probability entails.