Population and sample size Target population and sample size The population for this study will mainly be student body of Deakin University, Australia. This study will involve the input of mostly continuing students, faculty and post graduates with a few from the alumni association. The population can be stratified with continuing students, faculty and alumni placed into distinct groups to provide a clear picture of their thoughts on shortcomings of the university. With this level of diversity within the population, relevant measures will be adopted to address the varied issues that together make Deakin University less attractive (Thompson, 2004)1.
A majority of the sample size should however be allotted to the continuing students since they encounter the said challenges in their everyday encounters at the institution and have an updated first hand information that the alumni and members of the faculty may not be privy to, for this 70% of the respondents should be students. To make a decision on the sample size, one has to begin with the determination confidence level which is the level of closeness of the study in relation to real life.
An example is a case of an opinion poll on a presidential candidate that if found to be 80% at 2%confidence interval, then it implies that the true proportion was between 70 and 82 percent (Chen & Bai, 2004)2. To get a proper opinion on the issues under study at the university, then a Z score must be decided, a Z score is the amount of standard deviation from the average range. In this case, a confidence level of 95 percent is desirable.
A 95% confidence level has 3.92 standard deviations, which is 1.96 on either side so the Z-score then becomes 1.96 (Dattalo, 2008)3. The next stage is a prediction of the percentage the study will produce and in the case of this survey, 70 percent of the population is expected to agree with the hypothesis and therefore 60 percent of the percentage will be used. The following formula will be used to calculate the appropriate sample size (SS). SS = (Z^2*P*(1-P))/C^2 Where SS is the sample size, P percentage and C is the confidence interval. The above formula is populated with the values required and the total number of people necessary for the survey determined. Bibliography Chen, Z.
& Bai, Z. (2004). Ranked set sampling theory and applications. New York: Springer. Dattalo, P. (2008). Determining sample size: balancing power, precision, and practicality. Oxford: Oxford University Press. Thompson, W. L. (2004). Sampling rare or elusive species: concepts, designs, and techniques for estimating population parameters. Washington: Island Press.