Upon completion of this chapter, the student should be able to: - Define sampling.
- Document the historical connection between sampling and political polling.
- Describe and illustrate each of the following types of nonprobability sampling:
- reliance on available subject sampling,
- purposive (judgmental) sampling,
- quota sampling, and
- snowball sampling.
- Describe the role of informants in nonprobability sampling and provide advice for how to select them.
- Describe the logic of probability sampling, and include heterogeneity and representativeness in your response.
- List two advantages of probability sampling over nonprobability sampling.
- Define an EPSEM sample.
- Define each of the following terms and explain its role in probability sampling:
- element,
- population,
- study population,
- sampling unit,
- sampling frame, and
- parameter
- Differentiate a parameter from a statistic.
- Define sampling error and show how confidence levels and confidence intervals are used in interpreting sampling errors.
- Using probability sampling theory, describe the sampling distribution.
- Explain how to interpret a standard error in terms of the normal distribution.
- Explain why large-scale samples tend to make use of probability sampling.
- Restate the cautions regarding making generalizations from sampling frames to populations.
- Describe simple random sampling and list two reasons why it is seldom used.
- Summarize the steps in using a table of random numbers.
- Describe systematic sampling and employ the concepts of sampling interval, sampling ratio, and periodicity in the description.
- Link stratified sampling with the principle of heterogeneity and describe how this strategy is executed.
- Identify the major advantage of multistage cluster sampling and describe how this procedure is executed.
- Present guidelines for balancing the number of clusters and the cluster size in multistage cluster sampling.
- Explain why a researcher might use probability proportionate to size sampling and explain the logic behind this strategy.
- Outline the rationale for disproportionate sampling and weighting and note the dangers in using these strategies.
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