Probability sampling represents the best strategy for selecting research participants. The technique involves the random selection of several units from a population to represent the rest of the populace (Onwuegbuzie, & Collins, 2007). The probability of inclusion for each member of the population is determinable. The technique allows the researcher to use either random or stratified sampling methods. The sampling techniques present researchers with credible and valid representatives of the entire population.
When using a quantitative research approach, probability sampling allows the researcher to sample a large population since subjectivity is not required during the selection of the participants. The objective is to ensure that each individual has equal chances to be selected as a participant in the study. Random sampling allows the researcher to ensure that each member of the population has an opportunity to be chosen for the study (Teddlie & Yu, 2007). Probability sampling, therefore, validates the reliability of the research as it safeguards the transferability of the findings to other individuals for future study. Also, biasness is minimized due to the lack of subjectivity in the sampling methods. The research results are thus validated, and their reliability improved.
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Stratified sampling is useful in providing a more typical sample of the population to the researcher. It is based upon statistical information of the target population (Teddlie & Yu, 2007). For instance, if the researcher wishes to carry out a study on college students, a stratified random sample of both males and females would be necessary. The researcher would first separate the males and female students then take a stratified sample of each group for the study. The approach allows the researchers to classify the target population using characteristics relevant to the research. The research is thus more reliable.
Once the sampling is done, surveys can be used to collect data from the participants. Using surveys to collect data has the benefit of giving reliable data to the researcher (Nayak, & Narayan, 2019). The surveys are usually standardized, and similar questions are given to the participants. The data collected using well-structured surveys is not only reliable but also ensures the validity of the findings. The method is most applicable in quantitative research. On the other hand, surveys are inflexible in that a single data collection instrument is used. It isn't very easy to obtain more information beyond the structured questions. The method is, therefore, unpopular in qualitative research.
The likely ethical issue that may arise during data collection using surveys is the lack of confidentiality. The protection of the participant’s data is the responsibility of the researchers. The use of study codes on data collection instruments can be an effective method of ensuring data security.
Validity and reliability are closely associated concepts in research. Both concepts are crucial in evaluating the quality of a study. Reliability is more about the consistency of a measure, while validity is about its accuracy (Drost, 2011). For instance, if further measurements or observations produce similar results, the measure can be said to be reliable. On the other hand, if an accurate description of the concept being measured is possible, then the measure can be said to be accurate.
References
Drost, E. A. (2011). Validity and reliability in social science research. Education Research and perspectives, 38(1), 105.
Nayak, M. S. D. P., & Narayan, K. A. (2019). Strengths and weakness of online surveys. IOSR Journal of Humanities and Social Science, 24(5), 31-38.
Onwuegbuzie, A. J., & Collins, K. M. (2007). A typology of mixed methods sampling designs in social science research. Qualitative Report, 12(2), 281-316.
Teddlie, C., & Yu, F. (2007). WITHDRAWN-Mixed Methods Sampling: A Typology With Examples. Journal of Mixed Methods Research, 1(1), NP1-NP1.
