Sampling
What is Sampling?
Sampling is the process of selecting units (e.g., people) from a population of interest so that by studying the sample, one can fairly generalize the results back to the population from which they were chosen.
What kind of Sampling Frame can I select?
Projects can employ non-probability or probability sampling. {hyperlink Trochim resource, below} The difference between the two is that probability sampling involves some type of random selection, while non-probability sampling does not.
Probability sampling techniques:
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Random sampling occurs when there is an equal chance of selection to an evaluation group. The key to random selection is that there is no bias involved in the selection of participants from a sample; participants are chosen completely at random.
- A stratified sample is a mini-reproduction of the population. Before sampling, the population is divided into characteristics of importance for the research (e.g., by gender, social class, education level, or religion. Then the population is randomly sampled within each category or level; for example, if 38% of the population is college-educated, then 38% of the sample is randomly selected from the college-educated population.
Non-probability sampling techniques:
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Convenience sampling occurs when evaluation subjects are selected because they are easiest to access or on the basis of convenience and not because they are representative of the entire population. For example, talking to all the nurses on one shift or in one department based on ease of accessing them or likelihood that they can be reached for the study.
- Purposive samples are non-representative subsets of some larger population and serve a very specific need or purpose. For example, having a specific group in mind, such as high-level hospital administrators.