What is Sampling in Research?
If you have come across the word “sample” or “sampling” and you are wondering what it means, then this article will provide you with the best information regarding sampling in research. Sampling is a procedure employed by a researcher to systematically select a unit or subset from a pre-defined population to participate or serve as a data source for an experiment or a research study.
Researchers use sampling because it is almost impossible to collect data from every element or individual in a population. Therefore, there is a need to select a sample from the population that acts as a representative of the whole population. There are two main sampling techniques used when selecting a sample, probability sampling or random sampling and non-probability sampling or non-random sampling. Don’t forget that our experts will be glad to help you select or determine the sample size for your dissertation, thesis, or capstone project if you are facing challenges.
Probability Sampling
Probability sampling involves random selection where every element or individual has a non-zero probability of been included in a sample. There are four main types of probability sampling, simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
Simple Random Sampling
In simple random sampling, elements are selected randomly, the probability of each element in the population been included in the study is equal. The population must be homogenous such that every element must have characteristics that meet the targeted criteria for the target population. Every element used must be mutually exclusive such that the elements do not have overlapping characteristics.
Systematic Sampling
In systematic sampling, participants or elements are selected in intervals after a random starting point. The researcher picks the first element or participant and sets an interval, and then he or she picks every nth element after the first element using the selected interval. The interval is calculated by dividing the population by the desired sample size.
Unlike in simple random sampling, the elements do not have an equal probability of been selected. This technique is used when the population is homogenous. Remember our professional statisticians assist researchers by offering sample size selection services/help in case you are stuck.
Stratified Sampling
Stratified sampling is mostly preferred when the population is heterogeneous. The population is divided into small sub-groups called Strata; the strata formed are homogeneous such that the elements possess the same characteristics. A sample is drawn from each stratum using systematic or random sampling. These subsets of the strata then form a random sample. A researcher selects subgroups based on criteria such as gender, age, ethnicity, and occupation.
There are two allocation techniques used to allocate a sample from a stratum: The proportional allocation and equal allocation technique. The proportional allocation sets the sample size in a stratum to be proportional to the number of elements in the population. The equal allocation technique draws the same number of participants from each stratum regardless of the number of elements in the population.
Cluster Sampling
The population is divided into groups called clusters based on the geographical allocation, such as districts. The clusters should be homogeneous and capture the heterogeneity of the population. The researcher selects a number of the clusters to use as the sample using simple random sampling or systematic sampling where research, experiments, or observations are performed on these clusters. This method is mainly used when the elements in a population are spread through a wide geographical area.
Non-Probability Sampling
In non-probability sampling, elements or participants are selected using non-random criteria and they do not have an equal chance of been selected to participate in a study. This technique is suitable for qualitative or exploratory research where the aim is to get an understanding or idea and not to make statistical inferences about a population. There are four main types of non-probability sampling, convenience sampling, snowball sampling, quota sampling, and purposive sampling.
Convenience Sampling or Accidental Sampling
In convenience sampling, the members of the target population who meet certain criteria such as willingness to participate, easy accessibility, availability, or convenience are selected for the study. This technique has a generalizable aspect because one cannot tell if the selected sample is part of the population. Convenience sampling is prone to systematic errors and sampling bias.
Snowball Sampling
Snowball sampling is used in populations that are difficult to access, such as secret societies. The researcher uses the existing participants to recruit or refer other participants for the study, as the sample grows the researcher can collect enough data for the study. The sample generated is not a representative of the population therefore it is difficult to make statistical inferences about the whole population.
Quota Sampling
Quota sampling is mainly used when the population is heterogeneous. Homogeneous subgroups or quotas are created and a sample is drawn non-randomly from each quota. The aim is to create a sample where the quota been studied is a representative of the entire population.
Purposive Sampling
In purposive sampling, a sample is selected based on the judgment of the researcher. A participant is selected deliberately due to their qualities or the type of data the researcher aims to collect. Unlike convenience sampling, the researcher decided on what needs to be known and selects participants who can provide the specific information.
Summary
Sampling is an important aspect of conducting a research study because it is impossible to collect information or data from the whole population. The sampling technique to use entirely depends on the type of analysis to be conducted. Probability sampling’s main aim is to make statistical inferences about a population, while non-probability sampling’s main aim is to get an idea about the population. You can get professional assistance with any part of your research from our experts; just join our live chat for more details.