How can analytic functions be applied to a subset of multiple time series (MTS) in a signal? (Select all that apply)

Question

Options

• ACalculating the total value across all sources
• BAggregating values from all MTS into a single time series
• CApplying separate calculations for each MTS in the subset
• DCombining all MTS to visualize in a single chart

• A
  9% (3)
• B
  72% (23)
• D
  19% (6)

Explanation

Analytic functions applied to a subset of MTS can work in two distinct modes: aggregation (B) collapses multiple series into one by computing a combined value (e.g., sum, mean, percentile) across the subset, while per-series calculation (C) applies the function independently to each MTS, preserving individual series as separate outputs. Both are valid, supported patterns for scoping analytic functions to a subset rather than all MTS in a signal.

A is wrong because "total value across all sources" implies a global operation over every MTS, not a targeted subset - it also conflates a specific aggregation type (sum) with the broader concept of analytic functions.

D is wrong because combining MTS into a single chart is a visualization choice, not an analytic function operation - analytics concern computation, not rendering.

Memory tip: Think "BAG" - Batch-aggregate or Apply-per-series are your two analytic modes; A and D are distractors because one is too broad (all sources) and the other is about display, not math.

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