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It is often not possible or practical to study an entire population, so researchers draw samples from which they make inferences about a population of interest. In quantitative research, where generalization to a population is typically valued, a researcher’s ability to make such inferences is only as good as the sampling method she or he uses to obtain the sample. Although generalization is typically not a goal in qualitative research, sampling is no less important. Indeed, for quantitative, qualitative, and mixed methods research, sampling is a critical aspect of the research process.
With a sampling strategy in mind, attention then turns to collecting data from the sample. Specific methods of data collection produce specific types of data that will answer particular research questions, but not others; so here, too, as covered in previous weeks, the research questions inform the type of data that are needed (numerical or non-numerical) and how the data will be obtained (e.g., interviews, experiments, document analysis, surveys, observations).
For this Discussion, you will consider sampling strategies. You will also explore the strengths and limitation of various methods of data collection and their ethical implications. Last, you will consider measurement reliability and validity in the context of your discipline.
Position A: Probability sampling represents the best method for selecting research participants.
Position B: Nonprobability (or purposive) sampling represents the best method for selecting research participants.
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