1. Quantitative research tends to require the use of relatively large samples. With that in mind, consider the strengths and weaknesses of purposeful, convenience, and random sampling approaches in quantitative research. Assume that you are an automobile manufacturing executive tasked with increasing sales in your state. You wish to evaluate the effectiveness of an incentive program for sales personnel implemented at 10 dealerships in medium-size cities and 10 dealerships in small cities. All you have at hand are archived records of the incentives received by the sales staff and of their respective sales transactions. What information, data, and variables do you choose to analyze as relevant to your evaluation? Why? Which of the GCU core quantitative designs (introduced in a previous course) would best fit your evaluation plan? Why? How much data do you need to analyze in order to reach a meaningful conclusion? Explain. Do you anticipate any logistic difficulties or ethical concerns? Explain.
2. Imagine again that you are an automotive manufacturing executive tasked with increasing sales in your state. You wish to assess the effectiveness of an incentive program for sales personnel implemented at 10 dealerships in medium-size cities and 10 dealerships in small cities. What three data collection approaches are most feasible for such a study? What are the most significant strengths and weaknesses of these data collection approaches? Why are these significant? What concerns do you have about the feasibility of implementing these approaches to data collection for this study? Explain. RES 832
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