Final answer:
The question involves understanding different sampling methods like stratified, random, and convenience sampling and their application in various study scenarios to ensure accurate and representative data collection.
Step-by-step explanation:
The subject matter of this question pertains to determining appropriate sampling methods for conducting surveys or studies in different contexts. For example, when selecting nurses from different units in a hospital, one might use a stratified sampling method to ensure representation from each nursing unit. Similarly, when assessing compliance in various departments, a random sample of locations might be chosen to generalize findings across the whole hospital. In educational research or polls, different sampling techniques such as simple random, systematic, or convenience sampling may be used based on the study design or practical constraints.
An important aspect of conducting such surveys is the representation of the population by the sample. In cases where a sample is drawn from a larger set, like the 150 nursing home residents chosen to assess the incidence of an infectious disease, the sample size should be large enough to reflect the population's characteristics. It's also crucial to note that when researchers select subjects they know personally, as in the second researcher's case, the method used is convenience sampling, which may raise concerns about the data's representativeness and potential biases.
In sum, the choice of sampling method impacts the success and validity of a study, and the design should suit the study's goals and the population's characteristics while aiming for the most unbiased and representative sample possible.