As a business analyst in a credit card company, you are asked to analyze Extended Large Credit dataset which includes information of credit card applicants. The upper management of this credit card company is willing to make a credit card application decision (Accept or Reject) in order to maximize the total annual charges. These customer records include information on the customer’s ➢ Annual household income (in thousand dollar) ➢ Household size ➢ # of years of post-high school education ➢ # of hour’s watching TV per week ➢ Age ➢ Gender ➢ If his/her credit limit exceeded in past 12 months ➢ Annual credit card charges The upper management has provided you as much information as they have, and it is up to you to determine the best methods to answering their questions. Your manager has also made it clear that it is crucial that you explain the analysis and calculations (if you did not apply a procedure, explain why you did not use it) in such a way that a group of people unfamiliar with quantitative analysis can understand your findings. If you just provide a numerical answer to their questions, while still helpful, this will not meet the expectations for the project. Deliverable Your manager has requested that you answer their questions in the form of a business report in MS Word format. Simply typing in answers to their questions below will be construed as a lack of professionalism. The writing must be free of errors and easy to understand for someone unfamiliar with quantitative analysis. The exact design of the report is up to you, as upper management does not really care about the aesthetics as long as you answer all of their questions in an organized and coherent report. The upper management specifically requests that you include any equations and calculations that you had done to be completely transparent. Any graphs or diagrams can be included in the body of the report with an appropriate title.

Questions:

1. Provide an overview of the credit card customers by finding the descriptive statistics of each variable (each variable separately). In descriptive statistics, you may find the average, mode, median, variance, standard deviation, minimum and maximum values. Please keep in mind that the descriptive statistics metrics may not be meaningful for all type of data. For instance, calculating average of account number will not make any sense or mode and median may not explain details of the dataset and they may not be useful compared to other metrics.

2. Upper management also asked you to compare the variability of each variable and provide an analysis about which variable has more variability. If you used a specific metric to compare the variabilities of each column, explain why you did use that method.

3. You were also asked to provide an outlier analysis by creating box and whisker plot for the following variables (columns) (Please create box and whisker plot for each variable separately): ➢ Annual Income (x1) ➢ Hours Per Week Watching TV (x3) ➢ Annual Charges (y) Is there any outlier?

4. You were also asked to confirm your findings in Part 3 by computing the outliers for the same variables by using Inter Quartile Range method.

5. Upper management has asked you to construct a pivot table and pivot chart showing

a. Annual Charges in rows and group annual charges (each group width must be $12,000)

b. Household size in columns and group the household size by 3. Interpret the pivot table/chart.

6. You are also asked to create two more pivot table/chart (you can pick any variable, any group size, any variable in rows and columns etc.). The rows/columns in your pivot table must be different than Part 5.

Explain why you picked these pivot table? What does pivot chart tell us about the dataset? Please remember data visualization is very useful if they provide us a story about the dataset, if your graph and pivot table is not clear and not explaining data well, it will not be useful.

Answer rating: 100% (QA)

Answer Overview of Credit Card Customers This report provides an overview of credit card customers by finding descriptive statistics of each variable Descriptive statistics are used to summarize data ... View the full answer