What technique is used to assign probabilities in empirical distributions?

The relative frequency method is the correct technique used to assign probabilities in empirical distributions. This method relies on actual data collected from observations or experiments. By calculating how often a specific outcome occurs within a given set of data, we can derive probabilities based on this empirical evidence. Specifically, the probability of an event is determined by the number of times the event occurs divided by the total number of observations.

In contrast, theoretical estimation involves assigning probabilities based on a model or assumptions rather than actual data, which does not apply to empirical distributions. Random sampling refers to the process of selecting individuals or items from a larger population to make inferences about that population; while it is a critical step in gathering data, it does not directly relate to how probabilities are assigned after the data is collected. The term maximal conjecture does not pertain to probability assignment in empirical distributions, as it is not a recognized method in statistical analysis. Thus, the relative frequency method effectively captures and represents the probabilities based on real-world data.