Types of probability sampling techniques with examples
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Sampling Methods can be classified into one of two categories:
Probability Sampling: Sample has a known probability of being selectedNon-probability Sampling: Sample does not have known probability of being selected as in convenience or voluntary response surveys
Probability Sampling
In probability sampling it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected. The following sampling methods are examples of probability sampling:
Simple Random Sampling (SRS)Stratified SamplingCluster SamplingSystematic SamplingMultistage Sampling (in which some of the methods above are combined in stages)
Of the five methods listed above, students have the most trouble distinguishing between stratified sampling and cluster sampling.
Stratified Sampling is possible when it makes sense to partition the population into groups based on a factor that may influence the variable that is being measured. These groups are then called strata. An individual group is called a stratum. With stratified sampling one should:
partition the population into groups (strata)obtain a simple random sample from each group (stratum)collect data on each sampling unit that was randomly sampled from each group (stratum)
Stratified sampling works best when a heterogeneous population is split into fairly homogeneous groups. Under these conditions, stratification generally produces more precise estimates of the population percents than estimates that would be found from a simple random sample. Table 3.2 shows some examples of ways to obtain a stratified sample.
Table 3.2. Examples of Stratified Samples
Example 1Example 2Example 3PopulationAll people in U.S.All PSU intercollegiate athletesAll elementary students in the local school districtGroups (Strata)
4 Time Zones in the U.S. (Eastern,Central, Mountain,Pacific)
26 PSU intercollegiate teams11 different elementary schools in the local school districtObtain a Simple Random Sample500 people from each of the 4 time zones5 athletes from each of the 26 PSU teams20 students from each of the 11 elementary schoolsSample4 × 500 = 2000 selected peop
Probability Sampling: Sample has a known probability of being selectedNon-probability Sampling: Sample does not have known probability of being selected as in convenience or voluntary response surveys
Probability Sampling
In probability sampling it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected. The following sampling methods are examples of probability sampling:
Simple Random Sampling (SRS)Stratified SamplingCluster SamplingSystematic SamplingMultistage Sampling (in which some of the methods above are combined in stages)
Of the five methods listed above, students have the most trouble distinguishing between stratified sampling and cluster sampling.
Stratified Sampling is possible when it makes sense to partition the population into groups based on a factor that may influence the variable that is being measured. These groups are then called strata. An individual group is called a stratum. With stratified sampling one should:
partition the population into groups (strata)obtain a simple random sample from each group (stratum)collect data on each sampling unit that was randomly sampled from each group (stratum)
Stratified sampling works best when a heterogeneous population is split into fairly homogeneous groups. Under these conditions, stratification generally produces more precise estimates of the population percents than estimates that would be found from a simple random sample. Table 3.2 shows some examples of ways to obtain a stratified sample.
Table 3.2. Examples of Stratified Samples
Example 1Example 2Example 3PopulationAll people in U.S.All PSU intercollegiate athletesAll elementary students in the local school districtGroups (Strata)
4 Time Zones in the U.S. (Eastern,Central, Mountain,Pacific)
26 PSU intercollegiate teams11 different elementary schools in the local school districtObtain a Simple Random Sample500 people from each of the 4 time zones5 athletes from each of the 26 PSU teams20 students from each of the 11 elementary schoolsSample4 × 500 = 2000 selected peop
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