Course Project: AJ DAVIS DEPARTMENT STORES

Course Project: AJ DAVIS DEPARTMENT STORES

AJ DAVIS is a department store chain, which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables.

1. Location (rural, urban, suburban)
2. Income (in $1,000's—be careful with this)
3. Size (household size, meaning number of people living in the household)
4. Years (the number of years that the customer has lived in the current location)
5. Credit balance (the customers current credit card balance on the store's credit card, in $).

The data is available in Doc Sharing Course Project Data Set as an Excel file. You are to copy and paste the data set into a Minitab worksheet. 

• Open the file MATH533 Project Consumer.xls from the Course Project Data Set folder in Doc Sharing.
• For each of the five variables, process, organize, present, and summarize the data. Analyze each variable by itself using graphical and numerical techniques of summarization. Use minitab as much as possible, explaining what the printout tells you. You may wish to use some of the following graphs: stem-leaf diagram, frequency or relative frequency table, histogram, boxplot, dotplot, pie chart, bar graph. Caution: Not all of these are appropriate for each of these variables, nor are they all necessary. More is not necessarily better. In addition, be sure to find the appropriate measures of central tendency and measures of dispersion for the above data. Where appropriate use the five number summary (the Min, Q1, Median, Q3, Max). Once again, use minitab as appropriate, and explain what the results mean.
• Analyze the connections or relationships between the variables. There are 10 pairings here (location and income, location and size, location and years, location and credit balance, income and size, income and years, income and balance, size and years, size and credit balance, years and Credit Balance). Use graphical as well as numerical summary measures. Explain what you see. Be sure to consider all 10 pairings. Some variables show clear relationships, while others do not.
• Prepare your report in Microsoft Word (or some other word processing package),integrating your graphs and tables with text explanations and interpretations.Be sure that you have graphical and numerical back up for your explanations and interpretations. Be selective in what you include in the report. I'm not looking for a 20-page report on every variable and every possible relationship (that's 15 things to do). Rather, what I want you do is to highlight what you see for three individual variables(no more than one graph for each, one or two measures of central tendency and variability (as appropriate), and two or three sentences of interpretation). For the 10 pairings, identify and report only on three of the pairings, again using graphical and numerical summary (as appropriate), with interpretations. Please note that at least one of your pairings must include location and at least one of your pairings must not include location.
• All DeVry University policies are in effect, including the plagiarism policy.
• Project Part A report is due by the end of Week 2.
• Project Part A is worth 100 total points. See grading rubric below.

Submission: The report from Part 4, including all relevant graphs and numerical analysis along with interpretations

Format for report:

1. Brief introduction
2. Discuss your first individual variable, using graphical, numerical summary, and interpretation
3. Discuss your second individual variable, using graphical, numerical summary, and interpretation
4. Discuss your third individual variable, using graphical, numerical summary, and interpretation
5. Discuss your first pairing of variables, using graphical, numerical summary, and interpretation
6. Discuss your second pairing of variables, using graphical, numerical summary, and interpretation
7. Discuss your third pairing of variables, using graphical, numerical summary, and interpretation
8. Conclusion