Performing quantitative research is impossible without gathering and analyzing appropriate data. However, the research process may become complicated due to possible confusion of population with a sample, since both notions can be erroneously perceived as a group subjected to research. Therefore, it is necessary to understand an important difference — while population refers to an entire group, the sample encompasses only a specific group selected within the population for research purposes. Consequently, sampling can be defined as a method used to select a required sample from the whole population.
Several sampling methods are empirically distinguishable and can be used depending on the researcher’s needs. In general, all commonly used methods can be separated into two techniques — probability and non-probability sampling (Sharma, 2017). Probability sampling utilizes random selection from the population, which makes it more accurate, whereas non-probability sampling is based on judgment. Furthermore, probability-based methods can be divided into simple random sampling, systematic sampling, stratified sampling, and cluster sampling (Sharma, 2017). All these methods have their advantages and flaws — for instance, simple random, an independent selection of subjects, is easy and unbiased but limited to smaller populations. On the other hand, the method of cluster sampling is feasible for large populations since it uses naturally occurring groups as subjects (Sharma, 2017). However, it is also highly susceptible to selection bias and sampling errors.
The same situation applies to various non-probability sampling schemes. Quota, purposive, self-selection, and snowball sampling offer certain advantages, such as speed, the possibility to make generalizations, or access to hidden populations (Sharma, 2017). However, this utility comes at the increased cost of research bias and sampling errors. Regardless of an appropriate sampling technique, one should understand that sample consists only of a fraction selected from the population. In this regard, sampling must be perceived as a means of extracting the necessary fraction from the whole group.
Reference
Sharma, G. (2017). Pros and cons of different sampling techniques. International Journal of Applied Research, 3(7), 749-752.