(LO 1-6) Consider the 2013 rejected loan data from LendingClub titled “DAA Chapter 1-2 Data” from Connect Additional Student Resources. Browse the file in Excel to ensure there are no missing data. Because our analysis requires risk scores, debt-to-income data, and employment length, we need to make sure each of them has valid data. There should be 669,993 observations.

a. 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 if–then statements to complete this. Or sort by risk score and manually input into appropriate risk score buckets.

b. Run a PivotTable analysis that shows the number of loans in each risk score bucket.

Which risk score bucket had the most rejected loans (most observations)? Which risk score bucket had the least rejected loans (least observations)? Is it similar to Exhibit 1-14 performed on years 2007–2012?