Sampling MethodsKatie Rommel-Esham

Education 504

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 • Likelihood of being selected for the sample is not

known

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

Non-probability Sampling (con’t)

• Quota Sampling

• Non-random sample chosen to be representative of a particular group