An analyst is examining data from an array of temperature sensors and sees that one...

→ A systematic error is a consistent, repeatable error caused by faulty equipment or flawed measurement techniques. Since one sensor consistently over-reports values, this is a classic case of systematic error.

Why the other options are incorrect:

A: Synthetic data is artificially generated — unrelated to sensor malfunction.

C: Heteroskedasticity refers to non-constant variance — not consistent bias.

D: Idiosyncratic errors are random and unpredictable — not consistent.

Official References:

CompTIA DataX (DY0-001) Study Guide – Section 1.4:“Systematic errors arise from consistent biases in measurement devices or methods, requiring calibration or correction.”

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