A company is analyzing a dataset of customer transactions to detect potential credit card fraud. Which data analytics technique would be MOST appropriate for identifying transactions that deviate significantly from established patterns?

Answer options:

Regression Analysis

Cluster Analysis

Anomaly Detection

Sentiment Analysis

How to approach this question

Match the goal to the technique. Goal: Find 'weird' stuff. Technique: Anomaly Detection.

Full Answer

C.Anomaly Detection✓ Correct

Anomaly detection (or outlier detection) is the specific branch of analytics used to find rare items, events, or observations which raise suspicions by differing significantly from the majority of the data.

Common mistakes

Choosing Clustering (which groups data) instead of Anomaly Detection (which finds what doesn't fit a group).

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