Introduction
For each scientific research, clear and planned actions are necessary to achieve the best result. Previous work on the safety of fire services considered literary sources that can help the progress of the work. This paper explores such an aspect of the experiment as the definition of the sample and its plan. Moreover, the paper analyzes such concepts as possible and impossible sampling and defines a method for working with the population.
Sample Plan
Sample Unit
First, it is necessary to consider such a concept as a sampling plan. It is an outline of actions that become the basis for future research and especially concerns the selected population. The three main aspects that are included in this plan are the sampling unit, which shows the selected population, its size, and sampling procedures, which include various methods for selecting a population. The sampling unit is the most practical step since it is its definition that can have a significant contribution to how further research will take place. Thus, employees of the fire department of City X will be selected as a population to conduct research on the safety of fire services. This will be all the staff who worked during the time period selected for the analysis.
Sample Size
The second step is to establish the population size for the experiment. It is emphasized that the larger the sample size, the higher the level of reliability, which is also essential to take into account when measuring the population (Bujang & Baharum, 2017). Hence, for the study, the sample size will include employees of the fire department of the city of X., and therefore, researchers try to cover as many samples as possible.
Sample Procedures
The last step is to choose a procedure for the study of the sample. In this study, a random sample may be the most reasonable approach. Its advantage is that it excludes such aspects as bias, which provides equal chances for participants to participate. However, this method also has its drawbacks, which must be taken into account when conducting the study. It manifests itself in the mandatory presence of a list of elements of the general population (Martino et al., 2018). The difficulty seems to be. that this list is not always easy to obtain, which can result in a complicated procedure for carrying out work.
Probability and Non-Probability Sample
Depending on the goal that the study wants to achieve, a probability and non-probability sample can be selected. The first type of sample includes the convenience sample, which selects the most accessible participants, the judgment sample, which takes into account the people with the most significant contribution to the study (Etikan & Bala, 2017). The third type, quota sample, examines a pre-determined number of participants divided into specific categories.
Probability samples, in turn, can also be divided into several types. A simple random sample, which was chosen to conduct a study on the safety of fire services, implies an equal chance of being selected for the participants of the experiment. Stratified sampling implies the division of the population into groups according to a specific criterion and further random selection of participants from these groups. Another type of sampling probability is the cluster sample, where the population is divided based on territorial location. Each type of sample performs different tasks and is selected based on the desired outcome by scientific researchers.
Conclusion
In conclusion, this scientific paper studied the main points of drawing up a sampling plan. Henceforth, it consists of three main points; the sampling unit, its size, and procedures related to the selection of participants. Moreover, such types of sampling as probability and non-probability and their kinds were considered. The implementation of all three aspects may be of particular importance not only for the course of the study but also may directly affect the results of the experiment.
References
Bujang, M. A., & Baharum, N. (2017). A simplified guide to determination of sample size requirements for estimating the value of intraclass correlation coefficient: a review. Archives of Orofacial Science, 12(1).
Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 00149. Web.
Martino, L., Luengo, D., & Míguez, J. (2018). Independent random sampling methods. Martino: Springer International Publishing.