Definition: Cluster sampling is a sampling technique where the entire population is divided into groups, or clusters and a random sample of these clusters are selected. All observations in the selected clusters are included in the sample.
One-stage, two-stage and multi-stage cluster sampling:
The population is divided in non-overlapping groups called clusters. Samples of clusters are selected. The clusters are the primary units of sampling. The members of the clusters are the secondary units.
1. If all the members of each selected cluster are included in our sample (of secondary units), the method is called a one-stage cluster sampling.
2. If we take a random sample of each selected cluster, the method is called a two-stage cluster sampling.
3. The secondary units may themselves be groups of tertiary units, and we carry on into sub sampling tertiary units from the selected secondary unit, etc. this is called a multi-stage cluster sampling scheme.
Examples:
1. Suppose an organization wishes to find out which sports Year 11 students are participating in across Australia. It would be too costly and take too long to survey every student, or even some students from every school. Instead, 100 schools are randomly selected from all over Australia.These schools are considered to be clusters. Then, every Year 11 student in these 100 schools is surveyed. In effect, students in the sample of 100 schools represent all Year 11 students in Australia.
2. Suppose that the Department of Agriculture wishes to investigate the use of pesticides by farmers in England. A cluster sample could be taken by identifying the different counties in England as clusters. A sample of these counties (clusters) would then be chosen at random, so all farmers in those counties selected would be included in the sample. It can be seen here then that it is easier to visit several farmers in the same county than it is to travel to each farm in a random sample to observe the use of pesticides.
3. For example, in surveying the performance of school children, the country may be divided into areas (which form the primary units), schools within the areas form the secondary units, the classes within the schools form the tertiary units and the children within the classes form the main objects of the study population.
One-stage, two-stage and multi-stage cluster sampling:
The population is divided in non-overlapping groups called clusters. Samples of clusters are selected. The clusters are the primary units of sampling. The members of the clusters are the secondary units.
1. If all the members of each selected cluster are included in our sample (of secondary units), the method is called a one-stage cluster sampling.
2. If we take a random sample of each selected cluster, the method is called a two-stage cluster sampling.
3. The secondary units may themselves be groups of tertiary units, and we carry on into sub sampling tertiary units from the selected secondary unit, etc. this is called a multi-stage cluster sampling scheme.
Examples:
1. Suppose an organization wishes to find out which sports Year 11 students are participating in across Australia. It would be too costly and take too long to survey every student, or even some students from every school. Instead, 100 schools are randomly selected from all over Australia.These schools are considered to be clusters. Then, every Year 11 student in these 100 schools is surveyed. In effect, students in the sample of 100 schools represent all Year 11 students in Australia.
2. Suppose that the Department of Agriculture wishes to investigate the use of pesticides by farmers in England. A cluster sample could be taken by identifying the different counties in England as clusters. A sample of these counties (clusters) would then be chosen at random, so all farmers in those counties selected would be included in the sample. It can be seen here then that it is easier to visit several farmers in the same county than it is to travel to each farm in a random sample to observe the use of pesticides.
3. For example, in surveying the performance of school children, the country may be divided into areas (which form the primary units), schools within the areas form the secondary units, the classes within the schools form the tertiary units and the children within the classes form the main objects of the study population.
Advantages:
1. Reduced costs,
2. Simplified field work and administration is more convenient.
3. Instead of having a sample scattered over the entire coverage area, the sample is more localized in relatively few centers (clusters).
Disadvantage
1. Less accurate results are often obtained due to higher sampling error than for simple random sampling with the same sample size. In the above example, you might expect to get more accurate estimates from randomly selecting students across all schools than from randomly selecting 100 schools and taking every student in those chosen.
1. Reduced costs,
2. Simplified field work and administration is more convenient.
3. Instead of having a sample scattered over the entire coverage area, the sample is more localized in relatively few centers (clusters).
Disadvantage
1. Less accurate results are often obtained due to higher sampling error than for simple random sampling with the same sample size. In the above example, you might expect to get more accurate estimates from randomly selecting students across all schools than from randomly selecting 100 schools and taking every student in those chosen.
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1 comment:
Shalini,
Hi there! Hope you are still into sampling, I’m genuinely sorry for the delay caused due to ‘internet access difficulties’ (at my end) in commenting to your post.
Resources that you provided are good; I hope you have checked their genuineness and reliability though. If there is no mention of any author, check for backing by good and reliable institutions.
One line that I came across in your post was:
The population is divided in non-overlapping groups called clusters.
When I read this line I had several questions in my mind. On what basis would one make the clusters? Would it be based on the objective of the study? Or the various aspects you are looking at in a sample? Would it be random or non-random? Just correct me if I’m wrong.
It’s good that you have pointed out many kinds of cluster sampling. But at the moment for this semester it’s not required. But as they say always ‘nothing you learn ever goes wasted’. So it doesn’t matter that you have written more, it’ll always be of some help or the other.
The examples given are also good, but I would have been happy to see examples that you came up with and not the ones that were given in the resources.
The uploaded picture in the post supports it well.
All in all satisfactory material on cluster sampling.
cya..will be waiting for your reply..!
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