Simple random sampling refers to a type of probability sampling technique where each unit of the population under study has equal chances of being selected to constitute the sample size. (Lone et al., 2017).
To select a simple random sample from the university, I would follow the six steps of creating a random sample: population definition; sample size determination; population listing; assignment of numbers; randomization; and sample selection. The university population is approximately 12,000 students. Since the standard deviation of the students’ population is unknown, I would use a confidence interval of 0.5 to account for a variety of likelihoods, and a confidence level of 95%. To avoid human interference and calculation errors, I would use the online sample size calculator to obtain an estimate of an appropriate sample size. Thus, the sample size (n) needed will be 372 students.
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In order to prevent repeated participation, bias by gender and year of study, the sample size will be stratified according to year of study and gender. Since the university offers up to six-year degree programs, the 372 sample will be divided by six such that from each academic year, 62 students will be interviewed (31 males and 31 females). Using the strata based on year of study and gender, the population will be listed and all units will be assigned with numbers. Using Microsoft Excel random number function, I will generate the random numbers for the male and female students from each year, who will be surveyed. Having obtain permission to access students’ contacts, I will then send the phone survey questions to the randomly selected students for data collection on satisfaction with campus food service.
References
Lone, H. A., & Tailor, R. (2017). Estimation of population variance in simple random sampling. Journal of Statistics and Management Systems , 20 (1), 17-38.
Response to a classmates’ posts.
Melissa Blackwelder
Hello Blackwelder, your post regarding collection of a simple random sample is quite insightful. As you have correctly opined, random number generator is a critical tool that can be applied in sample generation. As posited by Mendoza et al., (2021), through random number generator, a sequence of numbers can be reasonably predicted. In my post, I described a six step process of creating a random sample. In your future posts, it would be prudent to consider application of the process when generating simple random sample.
References
Mendoza, M., Contreras-Cristán, A., & Gutiérrez-Peña, E. (2021). Bayesian Analysis of Finite Populations under Simple Random Sampling. Entropy , 23 (3), 318.
