Research Methods
Student’s Name
Institutional Affiliation
Research Methods
Question 1
The difference in population and sample
In research work, the term population refers to the comprehensive group of objects or individuals that have common characteristics, which are of interest to the research team for scientific inquiry. The population of interest refers to the study’s target population on which the study is conducted (Majid, 2018). A suitable target population enables the researcher to generalize the study’ finding to the entire the larger population from where the study elements were drawn. Majid (2018) explains that in research protocol in clinical research studies, it is vital to identify the characteristics of the study target population to assist in conceptualizing the eligibility criteria, sampling techniques and the study setting. The population under study should also have reasonable access to the research team.
Further, the population often contains too many elements which can be challenging to study due to various constraints, including time and budgetary limits. Thus, there is a need to need to choose a sample that contains a lot of information about the specific population parameter. The relation between the sample elements and the larger populations should be such that they can allow the researcher to make correct inferences about the general population from the sample. The sample chosen should have a high degree of representativeness such that it shares as many characteristics with the population as possible to enable in generalizing the study findings to the population. The sample should also have a suitable size to allow accurate statistical analysis. Overall, the main difference between a population and sample is that while the population refers to the objects or individual with similar characteristics in a population, the sample is a subunit of the population.
Types of sampling techniques
Sampling refers to the processes involved in selecting statistically representative samples of elements from the population under study. The primary sampling techniques include probability sampling techniques such as stratified, systematic and random sampling and non – probability sampling methods such as snowball, convenience and quota sampling. Sampling is a vital tool as it provides researchers with a suitable number of individuals or elements for the study and also determines the data collection methods. Choosing the most suitable sampling method requires the researchers to consider factors such as accessibility, sample size and data collection timeframe. An appropriate sample should statistically represent the target population to ensure that the findings provide answers to the research question. Martinez- mesa et al. (2016) point out that poor sampling can lead to selection bias such that that the chosen are not an accurate representation of the population. In the non – probability sampling methods, the sample is collected without any probability framework. The selection is based on the convenience it offers or other criteria and allows the researchers to collect primary data easily. The selection is not fully randomized and can result in samples that are not an accurate representation of the study population. On the other hand, in probability sampling techniques, every element has the same probability of being included in the study allowing researchers to make accurate statistical references concerning the whole group. Probability samples lead to the most accurate results as they have a high likelihood of representing the population.
Question 2
Using your proposed dissertation, the type of sampling that would be most appropriate
The most appropriate sampling for my proposed dissertation is simple random sampling technique. In this sampling method, the study participants will have a high likelihood of representing the target population since they will be randomly selected from the population under investigation. Random sampling removes bias associated with selection procedures, and every member of the population has an equal chance of getting chosen. Whereas the sample members are selected by chance, the probability of selection is known. Moreover, the method is appropriate since including all members of the population is impossible and not feasible. Hoeven et al. (2015) explain that the technique is often the most preferred sampling strategy because of unbiasedness as well as providing an opportunity for evaluating the precision (reliability) of the estimates. Population subsets are chosen as representatives of the entire population. When random samples are gathered properly, precise inferences can be made about the population with high levels of confidence. Because the study sample is relatively small, the study will use a lottery method to select samples such that each element of the population will be given be assigned a unique number before the numbers are randomly selected. The sampling will allow room for error with a variance of 5% sampling error for a 95% confidence level. Due to the minimized relevance of bias and representativeness associated with random sampling, the study findings from this technique can be generalized.
How will you access this sample?
The study sample will be accessed by sending study participants questionnaires and conducting online surveys using resources such as survey monkey. Accessibility is a critical part of the sampling and process, and researchers are obliged to develop a realistic sampling frame for the target population that is practicable for the project. The target population is inherently crude because it usually comprises of participants who cannot be included in the study as they would violate the research, context, assumption and goals. Asiamah et al. (2017) explain that the accessible population is obtained after removing all elements from the target population that are not accessible during the study period; they are a final group from which the data is collected. Also, accessing some study participants is expensive and time-consuming. Therefore, refining the target population is necessary. For example, a vast population that is geographically dispersed and demographically mixed can be challenging for the research team to access the representative sample. In this study, the sampling ensured that the research team has reasonable access to the subsets of the population and entailed limiting sample to a specific region. Thus, the study sample will be accessed by sending questionnaires and conducting an online survey as it is practicable with the research context, assumption and goals in addition due to budget and time constraints.
References
Asiamah, N., Mensah, H. K., & Oteng-Abayie, E. (2017). General, Target, and Accessible Population: Demystifying the Concepts for Effective Sampling. The Qualitative Report, 22(6), 1607-1621. Retrieved from https://nsuworks.nova.edu/tqr/vol22/iss6/9
Majid, U. (2018). Research fundamentals: Study design, population, and sample size. Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal, 2(1), 1-7. doi:10.26685/urncst.16
Martínez-Mesa, J., González-Chica, D. A., Duquia, R. P., Bonamigo, R. R., & Bastos, J. L. (2016). Sampling: How to select participants in my research study? Anais Brasileiros de Dermatologia, 91(3), 326-330. doi:10.1590/abd1806-4841.20165254
Van Hoeven, L. R., Janssen, M. P., Roes, K. C., & Koffijberg, H. (2015). Aiming for a representative sample: Simulating random versus purposive strategies for hospital selection. BMC Medical Research Methodology, 15(1). doi:10.1186/s12874-015-0089-8