SOC221 Lecture Notes - Lecture 7: Cluster Sampling, Stratified Sampling, Oversampling
25 Jan 2016
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Document Summary
If done right, you can get accurate results from a sample. Distinction between the population of interest and the actual population defined by the sampling frame. Generalizations can be made only to the actual population. The manner in which the sample is drawn determined to what extent we can generalize from the findings. The capacity a study has for generalizing to the larger (defined) population helps to establish external validity. Essential for probability sampling, but can be defined for nonprobability sampling. Element or unit: a single case in the population. Population: all cases that a researcher is interested in. Sampling frame: the list of elements that the sample will be selected from. Sample: the elements (subset of a population) selected for investigation. Representative sample: a sample that contains the same essential characteristics as the population. Probability sample: a sample selected using a random process so that each case element in the population has a known likelihood of being selected.
