What is difference between Stratified Sampling and Quota Sampling?
Answers
Answer:
The main difference between stratified sampling and quota sampling is in the sampling method:With stratified sampling (and cluster sampling), you use a random sampling method With quota sampling, random sampling methods are not used (called "non probability" sampling).
Explanation:
As a very simple example, let's say you're using the sample group of people (yellow, red, and blue heads) for your quota sample. The top level of people is much closer, geographically to your location. Therefore, it would be cheaper for your study to use that top layer. Your sample of 6 is simply that top layer, although note that you are still sampling proportionally from each strata.
As a very simple example, let's say you're using the sample group of people (yellow, red, and blue heads) for your quota sample. The top level of people is much closer, geographically to your location. Therefore, it would be cheaper for your study to use that top layer. Your sample of 6 is simply that top layer, although note that you are still sampling proportionally from each strata.In a real world scenario, you might have to reach quotas within your samples (which is technically why it's called quota sampling). For example, let's say you are performing a promotions related study to include 600 people, and you are required to include 300 women. Your quota (300 women) would prevent you from using a typical random selection method, like simple random sampling, because you'll probably end up with something other than 300 women. Therefore, your selection method won't be probabilistic, and you'll be performing quota sampling.
As a very simple example, let's say you're using the sample group of people (yellow, red, and blue heads) for your quota sample. The top level of people is much closer, geographically to your location. Therefore, it would be cheaper for your study to use that top layer. Your sample of 6 is simply that top layer, although note that you are still sampling proportionally from each strata.In a real world scenario, you might have to reach quotas within your samples (which is technically why it's called quota sampling). For example, let's say you are performing a promotions related study to include 600 people, and you are required to include 300 women. Your quota (300 women) would prevent you from using a typical random selection method, like simple random sampling, because you'll probably end up with something other than 300 women. Therefore, your selection method won't be probabilistic, and you'll be performing quota sampling.Note that there are two types of quota sampling: uncontrolled (subjects are chosen any way you choose) and controlled (restrictions are imposed to limit your choice). In the above examples, your choice to include nearby participants would be uncontrolled and those imposed quotas would make the method controlled.
Answer:
The main difference between stratified sampling and quota sampling is that stratified sampling would select the students using a probability sampling method such as simple random sampling or systematic sampling. In quota sampling, no such technique is used.