You are a marketing manager for a company that makes ready-to-eat breakfast cereals. Your company recently initiated a loyalty program for consumers, which resulted in a large purchaser database. The brand managers are eager to mine the available data, which they can use to design more effective promotional programs. The management of your organization believes that to be effective, these programs have to take into account significant cross-region (i.e., the East Coast, the West Coast, the Midwest, and the South) purchase differences. Your task is to test the hypothesis that there are significant cross-region differences in purchasing patterns. Management has suggested that you use six different two-way comparisons (directly comparing each region with every other region), with each two-way comparison being suggested at the 5% level.
Assess how appropriate management’s proposed use of hypothesis testing would be to validate management’s belief in cross-region purchase differences.
Explain the goal of this hypothesis testing experiment.
Describe the mechanics of this hypothesis testing process.
Explain why the organization would go through the trouble of hypothesis testing in this situation. Support your discussion with relevant examples, research, and rationale.
You are a manager working for an insurance company. Your job entails processing individual claims filed by policyholders. In general, most claims are relatively minor, costwise, but a few are quite expensive. Each quarter, you compile a report summarizing key claims statistics that includes the number of claims submitted, the mean cost per claim, the median cost per claim, the proportion of claims being litigated, the number of emergency procedures, the proportion of men versus women, and the average age of claimants. Your measures are computed separately for the southern and northern regions, and you are interested in determining whether or not there are statistically significant differences between the two regions on each of the aforementioned measures.
Evaluate which comparisons would require the use of the t-test and which would use the chi-squared test.
Explain your answers. Support your discussion with relevant examples, research, and rationale.
In the past several weeks, you have been introduced to a range of statistical data analysis tools. Consider what you have learned in the context of progression of data, information, and knowledge. What are the specific techniques you would consider most helpful in transforming information into knowledge (as opposed to just translating data into information)? Support your discussion with relevant examples, research, and rationale.
The final paragraph (three or four sentences) of your initial post should summarize the one or two key points that you are making in your initial response.
