Introduction

Sampling is one of the most important tools of quantitative research, as it allows the researcher to draw conclusions about a population based on a representative sample. Among the methods that have been developed, Simple Random Sampling is considered the most classical and fundamental. Although it is not often applied exclusively in practice, it holds particular significance because it forms the basis upon which sampling theory was built. Its essence lies in the fact that all members of the population have exactly the same probability of being selected, which ensures fairness and objectivity in the selection process.

Description of the Method

Simple Random Sampling is applied when every individual in a population has an equal probability of being included in the sample. Selection can be carried out through various randomization techniques, such as drawing lots, using random number tables, or employing electronic random number generators. The main advantage of this method is that it prevents the researcher’s intervention or subjectivity, since the process relies solely on chance. Its application is particularly practical in small populations, where it is possible to construct a complete list of all members. For instance, a researcher wishing to study the opinions of students in a small faculty could compile a full list of all names and randomly select a number of participants, thereby ensuring that the resulting sample is representative.

Advantages of Simple Random Sampling

This method presents several important advantages. The most fundamental is its fairness and objectivity, since all members of the population have the same probability of being selected, thus reducing the risk of bias. Moreover, its logic is simple and easy to understand, which makes it an ideal example for teaching the foundations of sampling theory. The method also allows the full application of probability rules and statistical tools, enabling the researcher to draw generalizable and reliable conclusions. Provided that the basic conditions are met, the resulting sample is usually representative of the population, which strengthens the validity of the research.

Disadvantages of Simple Random Sampling

Despite its advantages, the method also presents certain disadvantages. One of the most important is the need for a complete sampling frame, that is, a list that includes all members of the population, something that is not always feasible in practice (Berndt, 2020). Another issue is the increased cost involved in the process, particularly when data collection is conducted through personal interviews or other resource-demanding methods. In addition, its proper application requires adequate knowledge of statistical analysis so that the researcher can manage the data correctly. Finally, there remains the risk of sampling errors, which may affect the accuracy of results, especially when the research is conducted on a large sample or under complex conditions (Taherdoost, 2016).

Conclusions

Simple Random Sampling is one of the most important sampling methods, combining simplicity with objectivity. It ensures equal chances of participation for all members of the population and offers statistical validity and reliability. Although practical difficulties, such as the requirement of a complete sampling frame and the higher costs involved, limit its exclusive use in practice, the method still retains significant theoretical and educational value. It remains an essential tool for understanding the principles of sampling and a valuable means for any researcher who wishes to base their conclusions on objective and scientifically grounded evidence.