Probability Sampling• Subjects are selected in such a way that the
researcher knows an individual’s likelihood of being selected
Probability Sampling (con’t)
• Simple Random Sampling
• Everyone has the same probability of being chosen for the sample, for example, drawing names out of a hat
Probability Sampling (con’t)
• Systematic Sampling
• Every “nth” member of the population is chosen, where n is the sampling interval
• The sampling interval is determined by dividing the number in the population by the percentage desired.
Probability Sampling (con’t)
• Stratified Sampling
• The sample is divided into different strata before sampling
• In proportional stratified sampling, the sample reflects and preserves the proportions of the strata in the population
• In non-proportional stratified sampling, the sample does not reflect the stratification of the population
Probability Sampling (con’t)
• Cluster Sampling
• Naturally occurring groups are selected, then individuals are randomly selected from those groups
Non-probability Sampling (con’t)
• Convenience Sample
• Sample is selected because of availability
• Includes preexisting groups such as classrooms, local schools, etc.
Non-probability Sampling (con’t)
• Purposive Sampling
• Subjects are selected because they are viewed as being particularly informative relative to the nature of the research
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