Which action is crucial in performing diagnostic analysis to identify reasons/causes of anomalies in historical data?

Question

Options

• ACollecting unrelated data and ignoring statistical trends
• BIgnoring demographic variations in the data
• CCollecting related data and demographics
• DAnalyzing data from isolated points in time

• A
  2% (1)
• B
  4% (2)
• C
  93% (43)

Explanation

Collecting related data and demographics (C) is the foundation of diagnostic analysis because anomalies rarely exist in isolation - understanding who is affected and what contextual factors surround the data is what transforms raw observations into explainable causes. Option A is wrong because unrelated data introduces noise and actively obscures patterns rather than revealing them. Option B is the opposite of good practice: demographic variations are often the explanation for anomalies, so ignoring them blinds you to root causes. Option D fails because analyzing isolated time points removes the longitudinal context needed to distinguish a true anomaly from normal variance - trends only emerge across connected time windows.

Memory tip: Think "D + C = Diagnosis" - you need the right Data (related, not random) plus Context (demographics, trends) to diagnose anything. If you're missing either, you're guessing, not analyzing.

No community discussion yet for this question.