Decision Making

 
In both for-profit and not-for-profit organizations, statistics are  critical pieces of information that allow decision makers to steer the  organization in directions that are in the organization’s best interest.  Data is acquired from many sources, some within the organization, and  some from outside the organization. The government tracks data on many  different aspects of society (including industrial output). The  following questions will guide your thinking about the uses of data and  information.

Select any one of the following starter bullet point sections. Review the important themes within the sub questions of each bullet point. The sub questions are designed to get you thinking about some of the important issues. Your response should provide  a succinct synthesis of the key themes in a way that articulates a  clear point, position, or conclusion supported by research.  Select a different bullet point section than what your classmates have  already posted so that we can engage several discussions on relevant  topics. If all of the bullet points have been addressed, then you may  begin to re-use the bullet points with the expectation that varied  responses continue.

In any business, the quality of decisions is often related to the  quality of information. For instance, effective product marketing  entails combining the right offering (keeping in mind that  products are bundles of attributes and different bundles, or  combinations of attributes, will appeal to different prospective buyers)  with the right target buyer group. Knowing what constitutes  the right offering and the right prospective buyer group usually  involves data analysis. In general, using data to shape or guide  business decisions entails a progression along the continuum of data → information → knowledge.

Determine the difference between data, information, and knowledge.  Define the point at which data become information and information  becomes knowledge.
Explain why meaningful and correct data analysis—statistics—is  important in using the volumes of available business data. Support your  discussion with relevant examples, research, and rationale.

Assume you are a marketing analyst working for a manufacturer of  ready-to-eat cereal. You are given detailed sales data for the past year  and asked to create a report showing the differences between the four  sales regions (north, south, east, and west) in terms of sales volume,  profitability, and changes in sales volume and profitability; marketing  expenditures and changes in marketing expenditures; and per capita sales  and marketing expenditures.

Evaluate which of the four types of data (nominal, ordinal, interval, and ratio) is the sales data you are working on.
Compare specific statistical techniques and charts you could use to  depict differences, specifically addressing each of the categories  constituting your report. Determine which techniques and charts you  would use. Then explain why you believe that the techniques and charts  you have chosen would be appropriate. Support your discussion with  relevant examples, research, and rationale.

You are analyzing the cross-store sales of a grocery store chain. As  part of your analysis, you compute two measures of central  tendency—mean and median. The mean sales are $358.4 million, and the  median sales are $163.1 million (per store). To quantify the average  sales per store, evaluate which of the two measures would you use and  why. 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.
Submission Details:

Your posting should be the equivalent of 1 to 2 single-spaced pages (500–1000 words) in length. 100% original, no plagiarism.