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Probability Sampling Importance for Successful Research

In the academic setting, the ideal for any study is a reliable and high-quality procedure that produces results that effectively represent objective reality. In other words, scenarios in which a statistical experiment was initially based on an incorrect, unrepresentative approach to measuring the quantity sought should be eliminated. For this purpose, there is a wide range of well-known proven techniques and methods, among which special attention should be paid to the probability sampling method. The possibility of applying such a concept to the study of the teacher’s role in today’s school community will be discussed in this writing.

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Strictly speaking, sampling is a specific portion of the general population that is used in research to save resources and reduce the number of participants. No doubt it is impossible to conduct a sociological survey among five hundred thousand Maltese to find out their attitudes on critical issues, but instead, it is sufficient to generate a sample that is fully representative of the trends and sentiments of the entire nation. In this case, the sample is said to have the property of representativeness, which according to some authors, can be interpreted as the presence of every type of community member in the sample (EDC, 2018). In particular, while the focus — as inclusion criteria — should be based on the research question, other factors should also have weight in the sampling design.

It is no secret that there are several standard techniques for creating a representative sample, not the least of which is the probability type. In general, samples can be created by some sort of articulated rule, by inclusion criteria, or by chance (Barratt, 2018). Thus, Barratt notes that probability sampling is a group of random sampling techniques that can include simple, systematic, stratified, or clustered techniques. Choosing a particular form should be a critical step for conducting a study, as appealing only to the simplest version of probability sampling may ultimately yield unrepresentative data.

To investigate an established question, namely the teacher’s role and perception in today’s school system compared to how it was a few decades ago, a working hypothesis must first be formed. Thus, it is expected that over time, attitudes toward the image of the teacher in the minds of schoolchildren have shifted from highly respectful to sassy and defiant behavior. Obviously, this assumption generates a legitimate solution: we need to gather a group of modern schoolchildren and students of past eras, survey their opinions, and process them statistically. A simple random sampling of every, for instance, the third student in the current class and a group of past-generation graduates might at first glance be an effective strategy. However, as Suter (2012) has repeatedly shown, an initially understandable sample can produce incorrect results, which would violate the study’s logic. In other words, such sampling does not take into account students’ personal, educational achievements, academic performance, number of classes attended, and the teacher who had a direct influence. Therefore, in order to design a more robust study, it is reasonable to reduce the general population to students who attended the same school that has maintained the same academic culture over time. Specific influences of an individual teacher — such as instances of bias or outright disrespect — that may affect students’ perceptions of teacher image can be inhibited by not focusing on one professional but by discussing the teaching staff as a whole. Next, the population is not homogeneous, so stratified sampling is an appropriate solution. All students in both the current and past graduating classes need to be stratified by performance and class attendance. From each stratum, an equal number of participants can be randomly isolated to take the public opinion survey regarding the teacher’s role. In this way, central threats to representativeness will be addressed and eliminated, and the results will be most reliable.


Barratt, H. (2018). Methods of sampling from a population. Health Knowledge. Web.

EDC. (2018). Evaluation tool — sample representativeness and nonresponse bias: Frequently asked question. Web.

Suter, N. (2012). Educators as critical thinkers. Web.

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