Sampling is the process of selecting a group of individuals from a population for studying. To study and characterize the whole population, sampling is used. It is a statistical tool that has implications in many fields. For example, if a student planning to conduct a project on social media influence among students in a specified area or an institution he can make use of the sampling methods. The population of his study area will be huge so he cannot complete the project on time by meeting all individuals in the population. SO here comes the help of sampling. He can take a sample from the population. This sample represents the whole population and can collect data from these samples and complete the project.
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Sampling Techniques are of different types. It is based on the goal set, the sampling techniques are selected. The three key factors in sampling are Population, Sample, and Sampling frame. The population includes all the members of a specified group. This group is selected for the study. Sample means the observations selected from the population. The collection of data is done from the sample. Each sample will have different strengths based on the goal of the sample. The sampling frame means the information lies and defines the dimensions of the universe. Each sample selected must possess some characteristics. The sample must be representing the whole population. The sample must be unbiased and accurate. It must be reliable and the size of the sample must be adequate.
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Different Sampling Techniques
There are a lot of sampling techniques that are used to collect data from a sample. These techniques are used to find out samples also. The selection of a sample from a huge population is based on sampling techniques. The sampling techniques can be divided into two subgroups. They are:
- Probability Sampling
- Non – Probability Sampling
Probability sampling is based on random selection. It helps to make statistical inferences. Probability sampling includes four types of techniques:
- Simple Random Sampling
- Cluster Sampling
- Systematic Sampling
- Stratified Random Sampling
Non-probability sampling is based on non-random selection. In non-probability sampling, the selection will be based on convenience or based on other criteria.
- Convenience Sampling
- Judgemental or Purposive Sampling
- Snowball Sampling
- Quota Sampling
The selection of Probability or non-probability sampling is based on various factors. It includes the scope of the study, the objective of the study, methods of collecting data, clarity in results, etc. Let us look at all these sampling techniques in detail.
- Simple Random Sampling
In this type of sampling, there is a chance of each observation being selected from the population. So every observation the population has an equal chance of being selected. In this technique, all samples will be given numbers sequentially and selected numbers randomly.
- Systematic Sampling
Systematic sampling is a technique where the researcher picks some observations from the population randomly and from that, the researcher selects each nth from the randomly selected items. If a researcher needs 25 samples from a population of 100, he will divide the total into 25 groups consisting of 4 observations and select the 4th from every group.
- Stratified Random Sampling
In this type of sampling, the whole population is divided into homogeneous groups called strata. And from these strata, the final sample is selected by the researcher. This enables an equal opportunity for the representation of all members.
- Cluster Sampling
In this technique also the whole population is divided into different clusters. Researchers use simple random sampling or systematic random sampling techniques to select random groups for data collection.
- Convenience Sampling
This is a non-probability sampling method. In this sampling technique, the sample is selected for convenience. The willingness of individuals to participate in the survey. The result may be biased and inaccurate because convenience is the key to this technique. Non-probability sampling techniques as a whole may be inaccurate.
- Quota Sampling
In this technique, the whole population is divided into subgroups. These subgroups are divided based on some traits, features, or interests. The researcher selects a sample from each subgroup.
- Judgment Sampling
In this sampling technique, the judgment of the researcher is used to find out the samples. The judgment or purpose of the researcher helps in the selection of the sample. This will help in saving time and also money.
- Snowball Sampling
In this sampling technique, the existing observations are asked to suggest new observations for the selection of the sample. This will increase the size of the sample like the snowball rolling. This is a method commonly used in social science
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Conclusion
Sampling techniques are used to find out particular details by using a survey. It is impossible to directly go to the whole population and collect data. For example the election surveys. There is a huge number of voters in a constituency and the researchers select a group of people from each booth and ask questions, based on this they publish results. These are sampling techniques and their types.
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