After reading chapter 16 on probability and nonprobability samples, I learned a lot on comparing different sampling techniques. When doing our semester project, if money was not an option, I would choose to do the stratified probability sample for research on Mt. Dew. I would use this sample because it is a more efficient sample compared to random sampling. The book gave an example about urban and rural groups having different attitudes about conservation, but members within each group hold similar attitudes. It said that with stratified sampling each group is internally homogeneous but there are comparative differences between each group. This initial example reminded me of how the campus at UWG was similar but divided. I would hope that the stratified sample will have the assurance that the sample will accurately reflect the population on the basis of criteria used for stratification. I know this sample has a high cost to perform, but since I have an “unlimited amount of money” I’m not worried. I like this sampling technique because it assures representatives from all different groups in the sample (i.e. all the different groups/clubs/Greek life etc... at UWG.) After this, characteristics can then be estimated and compared about how different students feel about Mt. Dew. I hope this would reduce variability in the sample size!
For our group projective, we will actually be using convenience sampling because of the very low cost and it can be extensively used. The main advantage is that we don’t need a list of respondents to use because we know the target is the UWG population of college students. We need large numbers of convenience samples quickly and economically so this nonprobability sampling procedures makes the most sense. However, we are going to be very careful that we get a collective sample from all of the UWG population. We know that basing our results on a specific sample is not accurate and would hinder our results.
