Examine the Considerations When Choosing a Sampling Method

Topics: Sampling, Stratified sampling, Sample Pages: 2 (682 words) Published: April 4, 2013
Examine the considerations when choosing a sampling method
There are many sampling methods when a researcher wants to find out some information or observation on the general public. Some of these methods are random sampling, quasi-random sampling, stratified random sampling, quota sampling, snowball sampling, convenience sampling and self selecting sampling. Random sampling is a sample in which the whole population have an equal chance of being selected. This involves using either random numbers or systematic sampling. Some strengths of random sampling are that everyone has an equal chance of being picked and it also avoids sampling bias. It is also very quick to do, unlike some other sampling methods like stratified random sampling. The weaknesses of random sampling are that there is no guarantee that it will be representative of the population and there will be more time planning than actually getting the results. Quasi-random sampling is where the people who are being picked at random are the 10th or 100th on the list of participants willing to be sampled. The researcher chooses which number that the participants will be chosen off. Some advantages of quasi-random sampling are that it is a fair chance and there is no sampling bias with it, positivist also like this because it is objective. Some disadvantages of quasi-random sampling are that a sampling frame is need, there might be a rate refusal and that there is no guarantee that people will want to be sampled. There is also stratified random sampling; this involves the population being put into smaller groups, the people in these groups have a share talents and characteristics and they are chosen to represent their layer in the study. Some strengths of stratified random sampling of that it captures the key population of the characteristics that they are looking for. It also avoids a sample bias. Some weaknesses of stratified random sampling is that is takes a lot of time because a sampling frame needs to...
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