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    A simple random sample meant to be a representation of the entire data population. Simple random sampling is generally used when there is not much information about a population, or the data is very diverse and not easily grouped into subgroups.

    A stratified sampleusually separates the population into groups or strata with the same characteristic. A random sample is then picked from each group for the survey or interview. Stratified sample could be used if you want to compare subgroups within a population. For example, the researchers may divide a population into groups of men and woman. 

    A cluster sampling divides the population into sections or clusters. Then a section is randomly picked and everyone within that section is used for the survey or interview. Cluster sampling may be used in marketing such as an airline selecting 10 passengers from each full flight to do a questionnaire.

    In systemic sampling a starting point is randomly picked and from there every third or fourth person in the sample is picked. This can be used in any setting. In a hospital, the study conductor can ask every other room about their opinions on the hospital.

    In convenience sampling results are collected in whatever way is easiest for the surveyor. For example, if the surveyor wants to see which candidate will win in an election, she may ask all the people she already knows who they are going to vote for (Visual Learner, n.d.).


    Visual Learner. (n.d.). Retrieved March 23, 2017, from

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