The auditor of a credit bureau wants to verify that credit scores are between 100 and 800. Which two nodes would accomplish this task? (Choose two.)

Question

Options

• AEvaluation node
• BData Audit node
• CAnalysis node
• DStatistics node

• A
  2% (1)
• B
  94% (44)
• C
  4% (2)

Explanation

Options B and D are correct because both nodes directly surface the minimum and maximum values of a variable: the Data Audit node is purpose-built for data quality checks, flagging out-of-range values, missing data, and anomalies against defined thresholds - making it ideal for confirming scores stay within 100–800. The Statistics node generates descriptive statistics (including min/max), which lets the auditor immediately spot any score that breaches those bounds. The Evaluation node (A) is used to compare predictive model performance (like comparing two scoring models), not to validate raw data ranges. The Analysis node (C) performs higher-level exploratory or inferential analysis, not targeted range-boundary checks.

Memory tip: Think "Audit = Quality Guard, Statistics = Numbers at a Glance" - if you need to catch bad data, you Audit it; if you need to see the range, Statistics shows you the min/max instantly. Both tell you if a value crossed a boundary.

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