Problem #1.
A crucial step in the data analytics process is to answer important questions using available datasets. Browse all datasets provided by the World Bank at https://data.worldbank.org.
Find one dataset (for example, the GDP of all countries in 2018, the literary rate of all African countries from 2000 to 2018, etc.) that you are most interested in. List three questions that may be answered by analyzing this dataset. You only need to propose the questions. You do not need to provide any answers to these questions. Download and save the dataset in excel format. Type the name of the dataset along with the three potential questions in a word file.
Problem #2.
Use the LendingClub dataset provided in this week’s assignment folder named RejectedLoansAll.xlsx, perform the following procedures:
1) Select all rejected loans with Application Year = 2011 and delete the rest of the loans.
2) Construct six buckets (labelled Risk_Score_Bucket) for risk scores with the following coding scheme:
Excellent: Risk_Score>=800
Very Good: 760<=Risk_Score <800
Good: 700<= Risk_Score <760
Fair: 640<= Risk_Score<700
Poor: 600<= Risk_Score <640
Very Bad: Risk_Score <600 (this includes observations where Risk_Score is
missing)
3) Create a PivotTable that shows the number of loans, the average of Amount Requested, and the average of Debt-to-Income Ratio for loans in each of the six risk score buckets.
