For example, if you wish to report about differences between men and women at the end of your study, you should ensure that your sample doesn’t contain only women. A representative sample resembles important characteristics of the population from which it was drawn, in ways that are important for the research being conducted. We care about a potential participant’s likelihood of being selected for the sample because in most cases, researchers use probability sampling techniques to identify a representative sample from which to collect data. Unlike nonprobability sampling, probability sampling refers to sampling techniques for which a person’s likelihood of being selected from the sampling frame is known. We’ll explore those unique goals and techniques in this section. The goals and techniques associated with probability samples differ from those of nonprobability samples. While there are certainly instances when quantitative researchers rely on nonprobability samples (e.g., when doing exploratory research), quantitative researchers tend to rely on probability sampling techniques. Quantitative researchers are often interested in making generalizations about groups that are larger than their study samples, which means that they seek nomothetic causal explanations. Identify the various types of probability samples, and describe why a researcher may use one type over another.Define generalizability, and describe how it is achieved in probability samples.Describe how probability sampling differs from nonprobability sampling.
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