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. 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. 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 (opens in a new tab). 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. Run a PivotTable analysis that shows the number of loans in each risk score bucket