What characteristic defines random sampling?

Random sampling is defined by the principle that every combination of items from the sample set has a non-zero probability of being selected. This means that each item in the population has an equal chance of being chosen, ensuring that the sample is representative of the whole population. This characteristic helps eliminate bias in the selection process, making the results of the sampling more reliable and valid for generalization to the entire population.

In contrast, the other choices describe methods that introduce bias or limit the selection process. Selecting items based on predefined characteristics can lead to a skewed sample that does not accurately represent the diversity of the population. Considering only certain subsets of items narrows the scope and limits the randomness required for a true random sample. Finally, using a specific rule for choosing items can also introduce bias, as it might favor certain items over others, eliminating the equal probability aspect that defines random sampling.