What best describes an experiment in probability?

An experiment in probability is defined as a process that generates well-defined outcomes. This means that during an experiment, we can clearly identify the possible results that might occur when the experiment is conducted. For instance, if you flip a coin, you have a specific process (the flip) that leads to well-defined outcomes (either heads or tails). The clarity of outcomes is fundamental to the study of probability, as it allows one to analyze the likelihood of each outcome occurring.

In contrast, the other descriptions do not capture the essence of what an experiment is in the context of probability. Random outcomes with unlimited possibilities might refer to random events generally but do not define the structured nature of an experiment. A method for estimating population parameters pertains more to statistical inference rather than the execution of a probability experiment. Lastly, while a collection of possible outcomes (known as a sample space) is related to experiments, it does not describe the experimental process itself, which emphasizes the generation of those outcomes.