Types of Sampling
Any plan that relies on random selection is called a probability sampling plan (or technique). The following three probability sampling plans are among the most commonly used.
As the name suggests, the simplest probability sampling plan. It is equivalent to "selecting ball out of a bag". Each individual has the same chance of being selected.
2. Cluster Sampling
This sampling technique is used when the population is naturally divided into groups (also known as a cluster). For example, all the students in a university are divided into majors, all the bank accounts are divided into a bank branch, all the registered voters are divided into election districts.
In cluster sampling, we take a random sample of clusters and use all the individuals within the selected clusters as our sample. For example, in order to get a sample of the bank account whose bank account branch belongs to a certain city, you choose 5 branches at random from among all the branches in that city and use all the account in 5 selected branches as your sample.
3. Stratified Sampling
Stratified sampling is used when the population is divided into sub-population which we can stratum (plural strata). For example, all the students in a certain college are divided by gender or by year in college. In stratified sampling, we choose a simple random sample from each stratum, and our sample consists of all these simple random samples put together. For example, in order to get a random sample of the bank account whose account belong to a certain city, we choose a random sample of 50 accounts from each branch present in that city our sample consists of all these samples put together.
- Simple random sampling
- Cluster Sampling
- Stratified Sampling
As the name suggests, the simplest probability sampling plan. It is equivalent to "selecting ball out of a bag". Each individual has the same chance of being selected.
2. Cluster Sampling
This sampling technique is used when the population is naturally divided into groups (also known as a cluster). For example, all the students in a university are divided into majors, all the bank accounts are divided into a bank branch, all the registered voters are divided into election districts.
In cluster sampling, we take a random sample of clusters and use all the individuals within the selected clusters as our sample. For example, in order to get a sample of the bank account whose bank account branch belongs to a certain city, you choose 5 branches at random from among all the branches in that city and use all the account in 5 selected branches as your sample.
3. Stratified Sampling
Stratified sampling is used when the population is divided into sub-population which we can stratum (plural strata). For example, all the students in a certain college are divided by gender or by year in college. In stratified sampling, we choose a simple random sample from each stratum, and our sample consists of all these simple random samples put together. For example, in order to get a random sample of the bank account whose account belong to a certain city, we choose a random sample of 50 accounts from each branch present in that city our sample consists of all these samples put together.