Sampling is one of the most important methods that determine the accuracy of research. If the samples chosen for a study are not a good representative of a population, it may falsify the results. Non probability sampling is probability sampling that does not deal with diversified data. It is the opposite of random sampling, which focuses on subjective judgement. The use of this sampling technique can be seen frequently in research work. As per its frequent use, this article aims to discuss non probability sampling in detail.
What Are Sampling Techniques?
Sampling is a method that allows researchers to gather information about a population under study based on the information provided by the subsets; instead of investigating every individual. These subsets assist researchers in reducing the cost, effort, and time required to complete a study. There are several types of sampling techniques. These sampling techniques are divided into two groups, non-probability and probability sampling.
Probability sampling starts with selecting all suitable individuals, so each one has an equal chance to participate in a study. It aims to promote generalization in results. At the same time, in non-probability sampling, only a few eligible candidates are selected instead of all. Thus, we often miss some individuals who may be potential candidates for a study in the latter one.
Probability sampling further includes simple random sampling, systematic sampling, stratified sampling and clustered sampling. Similarly, non-probability sampling includes convenience sampling, quota sampling, judgment or purposive sampling, and snowball sampling. All these sampling techniques differ based on the selection of samples, sample size and grouping techniques. Let’s have a detailed discussion of each type of non probability sampling.
Convenience Sampling
One of the types of non probability sampling is convenience sampling which does not aim to follow a particular pattern. In this type, you are free to find the respondents at your ease. In this sampling technique, you can target any type of audience. It can be a street person or an employee in some reputable organization.
For example, you are unavailable to collect research data because of some reason. Also, you are running short on time. The recent situation of Covid pandemic can also fit best for this example. I have also experienced the situation of the pandemic and difficulties of data collection for research. In this case, the best sampling technique is convenience sampling. Here, you can ask your friends, peer and seniors to participate in your research work. Also, there is no need to go and visit every person individually, but you can share the research survey via mail or other social media platforms at your convenience.
Quota Sampling
Another type of non probability sampling is quota sampling which aims to go for a predetermined number of units. The portions of units you select for your study are named as a quota. One of the best approaches to use this sampling technique is to make subgroups which are named as strata. For making strata, you have to divide the selected population into exclusive groups. In each stratum, you are supposed to find the representative proportion and select the sample size accordingly. In this way, it becomes easy to reach the designed quota.
This type of non probability sampling usually works well to study the characteristics of a certain group. That is why, you can find its major use in research like social science and psychology.
As the number of respondents is reduced in quota sampling, so it is considered a cheap sampling technique. On the other hand, you may have to struggle to eliminate the factor of biasness. Many novel researchers have to face problems in this regard. If you are also dealing with the same problem, you can ask expert researchers working at dissertation help service. This approach can help you save much of your time.
Self-Selection Sampling or Volunteer Sampling
The self-selection sampling technique is more like purposive sampling. You have to spend quality time in finding people who are willing to respond to your research questions. Otherwise, there is no problem related to travelling and other stuff. You can communicate with the willing respondent through any mode of your choice. It can be an online platform or a posting platform. While using this type of non probability sampling, you have to put effort into the composition of the collected sample. One of the best use of self-selection or volunteer sampling can be seen in TV shows asking for participants in an event. Arceus X
Snowball Sampling
In a research study, when potential participants recruit other respondents, it is termed as snowball sampling technique. Every potential participant gets the chance to contribute to research, and you can better determine the hidden population with fewer efforts. The start of snowball sampling can be with two to three respondents, and the ball will keep getting big size.
At the time of collecting data through snowball sampling, researchers take it as a biased technique. In this case, you have to follow the precautions which can save you from biasness and help you end up with precise results. Another concern of novel researchers is about the ethical issue. So, I suggest you do not believe in myths but go for snowball sampling techniques and find results for your research.
Purposive Sampling or Judgmental Sampling
The purposive sampling technique is one which allows you to determine the characteristics required for your study, and you select units on purpose. This type of non probability sampling works well when you have to deal with a small sample size. For large sample size, it can cause errors and nonproductive data.
For example, a group of researchers aims to study a particular problem, and you find a typical point that can be the reason for some happing. This judgement is something which provides strength to purposive sampling,
Final Thoughts
The above-mentioned points can help you learn the effective use of non probability sampling techniques. Each type of non probability sampling has a particular role to play and deal with different sample size. Read and understand each type to make your research reliable.
