Final answer:
The 5% of subscribers who answered the magazine publisher's survey represents the sample. This low response rate can introduce bias and affect the reliability of the results, indicating a nonsampling error. Quota sampling, on the other hand, aims at representativeness, but can still be susceptible to similar issues.
Step-by-step explanation:
The 5% of subscribers who responded to the magazine publisher's survey represent C) The sample. A sample is a manageable number of subjects who represent a larger population, and in this case, these are the subscribers who chose to respond to the survey.
Considering that the response rate is very low, this may not be a representative sample of the entire subscriber base, thereby affecting the reliability of the survey results. This low response rate is likely to introduce biases into the survey findings, as it is possible that those who responded have different opinions or characteristics compared to those who did not respond, making the results less generalizable.
Problems arising from a low response rate like this are examples of nonsampling error, because they are issues that affect data collection and the interpretation of results, rather than stemming from the method of selecting the sample (which would be sampling error).
The contrast to this is quota sampling, which was used by another pollster in 1936, where researchers aimed to survey specific subsets of the population to ensure representativeness. However, even with quota sampling, if there is a low response rate or nonresponse bias, this can still lead to skewed results.