Answered step by step
Verified Expert Solution
Link Copied!

Question

1 Approved Answer

Consider the 2 0 1 3 rejected loan data from LendingClub titled DAA Chapter 1 - 2 Data . To prepare the dataset for analysis,

Consider the 2013 rejected loan data from LendingClub titled DAA Chapter 1-2 Data. To prepare the dataset for analysis, lets scrub the risk score data. First, because our analysis requires risk scores, debt-to-income data, and employment length, we need to make sure each of them has valid data.
Open the file in Excel.
Sort the file based on risk score and remove those observations (the complete row or record) that have a missing score or a score of zero, if needed.
Assign each risk score to a risk score bucket similar to the chapter. That is, classify the sample according to this breakdown into excellent, very good, good, fair, poor, and very bad credit according to their credit score noted in Exhibit 1-13. Classify those with a score greater than 850 as Excellent. Consider using nested ifthen statements to complete this. Or sort by risk score and manually input into appropriate risk score buckets.
Run a PivotTable analysis that shows the number of loans in each risk score bucket.
Required:
After removing the observations with a zero or missing risk score, which group (Excellent, Very Good, Good, Fair, Poor, Bad) had the most rejected loans (most observations)? Which group had the least rejected loans (least observations)? Is it similar to Exhibit 1-14 performed on years 20072012?

Step by Step Solution

There are 3 Steps involved in it

Step: 1

blur-text-image

Get Instant Access to Expert-Tailored Solutions

See step-by-step solutions with expert insights and AI powered tools for academic success

Step: 2

blur-text-image

Step: 3

blur-text-image

Ace Your Homework with AI

Get the answers you need in no time with our AI-driven, step-by-step assistance

Get Started

Recommended Textbook for

More Books

Students also viewed these Databases questions

Question

What is a verb?

Answered: 1 week ago