Bias

Bias in metrology is the systematic difference between the average measured value and the true (reference) value — a constant offset that affects accuracy (not precision), caused by calibration errors, measurement physics, or systematic instrument offsets.

Bias Assessment

  • Reference Standard: Measure a certified reference material (CRM) or NIST-traceable standard — compare the average measurement to the certified value.
  • Calculation: $Bias = \bar{x}_{measured} - x_{reference}$ — positive bias means the gage reads high.
  • Significance: Perform a t-test to determine if the bias is statistically significant — small biases may be within noise.
  • Correction: Apply a bias correction: $x_{corrected} = x_{measured} - Bias$ — calibration removes systematic bias.

Why It Matters

  • Accuracy: Bias is the primary component of measurement accuracy — precision (repeatability) and accuracy (bias) are independent.
  • Calibration: Regular calibration corrects for drift in bias — calibration intervals must prevent excessive bias accumulation.
  • Tool Matching: Bias differences between tools (CD-SEM #1 vs. #2) cause apparent process variation — matching requires bias alignment.

Bias is the systematic error — the constant offset between what the measurement tool reports and the true value, correctable through calibration.

Take bias further

Ask the copilot about this term, or have our engineers assess it against your process.