Wednesday, February 8, 2023

A Brief Detail of Pros and Cons of Different Sampling Methods

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Different sampling methods are used for different fields. Therefore, it is very important to use the right technique or method for sampling. In this article, we will learn what sampling is, the different types of sampling, and its pros and cons. Sampling is a technique that a researcher employs to systematically select a relatively smaller number of representative individuals or subsets from a calculated or expected population for the observation of his study or research. These methods include the following factors: the research objective, alteration in population, technique or method used for sampling, and precision in results. Sampling ensures high accuracy of data, low cost, less time consuming, and suitable in limited resources.

Types of Sampling Techniques

Snowball Sampling Technique

The Snowball sampling technique is a non-probability technique in which sample groups or participants look like a rolling snowball. In this method, the researcher contacts a few people who meet certain study criteria. After completing their study, each person recommends a few other people of the same study criteria. The researcher hopes the data collection reaches enough people for his study by building such a network.

Pros And Cons Of Snowball Sampling Technique

  • The Snowball sampling technique is a slow process.
  • It is a non-random approach
  • It is an effective method to study hard to reach people.

Quota Sampling

Quota sampling is the representation of participants to be studied as much as possible and used when you are unable to use probability sampling. Therefore, it is non-probability based, usually used when a researcher classifies subsets of the population that are significant to represent. It is much easier and quicker than the probability sampling method. Quota sampling aims to examine the difference between male and female students in a sample.

Pros And Cons Of Quota Sampling

  • It certifies the representation of important groups within the population being studied.
  • It has the potential for bias
  • It allows us to easily compare particular groups.

Simple Random Sampling

Simple random sampling is the basic type of probability sampling in which every member have an equal chance of being nominated for the study. In simple random sampling, each member selects independently against the population. The whole process of simple random sampling is done in a single step.

Pros And Cons Of Simple Random Sampling

  • Simple random sampling is a fair way of choosing a sample from a given population.
  • It has a strong external validity
  • It is expensive and time-consuming
  • It is efficient and faster than other sampling methods.

Systematic Sampling

Systematic sampling is a method of random sampling in which every population participant is given a number. Then the researcher arbitrarily picks one participant from the list as his first participant. After this, the researcher selects an interval, roughly 8, and samples every 8th individual on the list.

Pros And Cons Of Simple Systematic Sampling

  • It is less feasible as this method is impossible without a list of all participants.
  • It is simple and easier than a simple random method
  • It is faster than a simple random method and has external validity.

Cluster Sampling

Cluster sampling, also called multi-stage sampling, occurs when the researcher arbitrarily selects the sample or participant from a cluster or group of people. It does not require a sampling frame like random sampling. Cluster sampling is assembled into frames when the sample or cluster is selected.

Pros And Cons Of Cluster Sampling

  • It is feasible when you are dealing with a large population
  • It may generate a high chance of error compared to other probabilistic methods.
  • It is faster, more effective, and has external validity

Stratified Sampling

Stratified sampling is a method of making strata (a division of the population into smaller groups). Strata are formed on the basis of specific demographic groups. The researcher randomly chooses the samples when the categories are selected. If you want to learn more about the stratified sampling method, you may contact the best dissertation writers of a reliable dissertation writing service.

Pros And Cons Of Stratified Sampling

  • It ensures the adequate representation of small groups
  • It reduces the potential for human bias
  • It may not get adequate results if the population cannot be divided into separate subgroups

Conclusion

Sampling saves the time and money of a researcher by allowing them to gather the same answer from the sample as that of the population. It allows enough answers for a researcher to complete his research study. However, sampling has different methods having their pros and cons. Students can use these sampling methods to gather the data by knowing the pros and cons of their research investigation.

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