Final answer:
The characteristic not associated with a random sample is that the selection of any one case is dependent upon the selection of any other case, which would introduce bias into the sample.
Step-by-step explanation:
The characteristic that is NOT a part of a random sample is choice b: The selection of any one case is DEPENDENT upon the selection of any other case. In a random sample, each selection should be independent of any other; if the selection of one case affects the selection of another, it would introduce bias into the sample. The essential features of a random sample include all combinations being possible and every case having an equal chance of selection, which ensures that each member of a population has an equal likelihood of being chosen for the sample, making it representative of the population.
Random samples are an effective way to select participants for a study because they aim to be a representative subset of a population where each member has the same chance of being included. Sampling without replacement indicates that once a member of the population is selected, they are not replaced, making each pick unique and dependent on previous selections, exemplified by Figure 3.7 in your reference. This is not typical for many random sampling methods where each selection is ideally independent, but it's important to specify the context when discussing dependent or independent selection within sampling methods.