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I would like to understand the  ideas behind the different sampling techniques. 

First, I would like you to know that there are various sampling techniques and every researcher employs a technique that is convenient for their process, in other cases, organizations might require that their research is conducted with adherence to specific guidelines. I will therefore present you with the 5 sampling techniques that are used mostly. 

There are four types of sampling plans

1. Simple Random- here each item/element in the population has an equally likely chance of being selected.

2. Convenience - sample drawn is most convenient for the researcher

3. Systematic- every nth item/element is selected

4. Cluster- population is first grouped and then groups are selected at random. Every item in the group is used in the sample

5. Stratified- population is grouped into layers and a sample is drawn from each different layer

But then, why would someone sample objects before conducting the experiment?

We sample because in most cases it is not feasible to collect data on everyone in our population. A valid sample must represent the population. For example, if I am interested in knowing the average height of male students at MCC, my sample must represent make students at MCC. It would not make sense to measure male students at UMASS Lowell. They do not represent the population I am wishing to study.

 

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