Final answer:
From the scenarios provided, (a) and (b) could potentially contain nonbiased samples, depending on the initial selection in (a) and the demographic representation in (b).
Step-by-step explanation:
When discussing nonbiased samples, we are referring to samples that give each member of the population an equally likely chance of being chosen. In the scenarios provided:
- (a) This is a systematic sampling method, and it can be considered nonbiased if the first student was randomly selected and if there is no pattern in the list that might relate to GPA.
- (b) Using random number generator to select 1000 town residents ensures each member has an equal chance of being selected, making this a nonbiased sample.
- (c) Selecting a random group of students within a single classroom to estimate height may be biased due to lack of variability (e.g., all students in the same grade).
- (d) Collecting data by recording the salaries of professors in 12 randomly selected departments involves cluster sampling. It could be nonbiased if the departments were sufficiently diverse and represent the whole.
From the given scenarios, (a) and (b) appear to have nonbiased samples, provided (a)'s systematic approach started with a truly random initial selection and (b) truly represents the town's demographics.