Answer is Quota sampling.
Its one of the method of non-probability sampling.
There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.
1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling
Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sample is taken from each stratum, the sampling effort may either be a proportional allocation (each simple random sample would contain an amount of variates from a stratum which is proportional to the size of that stratum) or according to optimal allocation, where the target is to have a final sample with the minimum variabilty possible. The main difference between stratified and cluster sampling is that in stratified sampling all the strata need to be sampled. In cluster sampling one proceeds by first selecting a number of clusters at random and then sampling each cluster or conduct a census of each cluster. But usually not all clusters would be included.
Simple random sampling = A process of selecting subjects in such a way that each member of the population has an equal likelihood of being selected; you can throw all your subjects into a hat and draw them out one by one, or assign each member a number and choose every fifth number to be a participant.Probability sampling=A sampling procedure in which the probability that each element of the population will be included in the sample can be specified; you have a specific number of subjects and you know that they have a 50/50 chance of being chosen, or because of an anomaly, they may only have a 20/100 chance of being chosen for the experiment.*Your teacher is being tricky however, because there are 4 basic types of Probability sampling and simple random sampling is one of them. Also are stratified, systematic and cluster sampling. All four fall under the general title of Probability Sampling (P.S.)!! P.S. is kinda like the category and the 4 types are just different ways to do the sample, each has their own "little differences" in how the data is collected and assigned.
What is the difference between quota sampling and cluster sampling
They include: Simple random sampling, Systematic sampling, Stratified sampling, Quota sampling, and Cluster sampling.
Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling
There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.
1) Simple random sampling 2) Systematic sampling 3) Stratified sampling 4) Cluster sampling 5) Probability proportional to size sampling 6) Matched random sampling 7) Quota sampling 8) Convenience sampling 9) Line-intercept sampling 10) Panel sampling
cluster sampling, quota sampling, systematic sampling, stratified random sampling which one is correct?
simple random, stratified sampling, cluster sampling
Quota sampling stratified sampling random sampling convenient sampling cluster sampling semi stratified sampling stratified quota
Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sample is taken from each stratum, the sampling effort may either be a proportional allocation (each simple random sample would contain an amount of variates from a stratum which is proportional to the size of that stratum) or according to optimal allocation, where the target is to have a final sample with the minimum variabilty possible. The main difference between stratified and cluster sampling is that in stratified sampling all the strata need to be sampled. In cluster sampling one proceeds by first selecting a number of clusters at random and then sampling each cluster or conduct a census of each cluster. But usually not all clusters would be included.
Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sample is taken from each stratum, the sampling effort may either be a proportional allocation (each simple random sample would contain an amount of variates from a stratum which is proportional to the size of that stratum) or according to optimal allocation, where the target is to have a final sample with the minimum variabilty possible. The main difference between stratified and cluster sampling is that in stratified sampling all the strata need to be sampled. In cluster sampling one proceeds by first selecting a number of clusters at random and then sampling each cluster or conduct a census of each cluster. But usually not all clusters would be included.
This would be stratified; the two strata are ages of drivers < 30 & ages of drivers drivers >30.
Simple random sampling = A process of selecting subjects in such a way that each member of the population has an equal likelihood of being selected; you can throw all your subjects into a hat and draw them out one by one, or assign each member a number and choose every fifth number to be a participant.Probability sampling=A sampling procedure in which the probability that each element of the population will be included in the sample can be specified; you have a specific number of subjects and you know that they have a 50/50 chance of being chosen, or because of an anomaly, they may only have a 20/100 chance of being chosen for the experiment.*Your teacher is being tricky however, because there are 4 basic types of Probability sampling and simple random sampling is one of them. Also are stratified, systematic and cluster sampling. All four fall under the general title of Probability Sampling (P.S.)!! P.S. is kinda like the category and the 4 types are just different ways to do the sample, each has their own "little differences" in how the data is collected and assigned.
What is the difference between quota sampling and cluster sampling