Conveinience sampling IS a less reliable type of sampling

Conveinience sampling IS a less reliable type of sampling

4-Conveinience sampling IS a less reliable type of sampling.  Like the name, it it used for conveinience for the researcher.  It does not give a broader population of participants, narrowing down to a smaller group, or groups more than likely to answer similiarly.

 

5-Cluster sampling is when the population is divided into sections, then a section is chosen, and every individual of that section is used. An example would be to use classrooms A, B, C, and D, then choose one of those classrooms as your sample in the study.

Convenience sampling is used to get results by the easiest of ways. An example is when the researcher uses subjects close at hand.

Systematic sampling is having a place to begin and then selecting (every other, for example) of that sample. For example, lining up a class of 10 th graders and picking every 3 rd person to be part of the sample.

Stratified sampling takes a population with the same characteristics and divide it into two separate groups and then take a sample from each group. An example could be taking soccer players with similar playing capabilities dividing that population into two groups and then selecting players from each of those groups.  ”

 

6-Cluster sampling is when the population is divided into sections, then a section is chosen, and every individual of that section is used. An example would be to use classrooms A, B, C, and D, then choose one of those classrooms as your sample in the study.

Convenience sampling is used to get results by the easiest of ways. An example is when the researcher uses subjects close at hand.

Systematic sampling is having a place to begin and then selecting (every other, for example) of that sample. For example, lining up a class of 10 th graders and picking every 3 rd person to be part of the sample.

Stratified sampling takes a population with the same characteristics and divide it into two separate groups and then take a sample from each group. An example could be taking soccer players with similar playing capabilities dividing that population into two groups and then selecting players from each of those groups.

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