Understanding Coefficient of Variation
How we calculate. CV % = σ ÷ μ × 100 (or sample s ÷ x̄ × 100). The form uses the same arithmetic as the worked examples on this page. See our methodology and accuracy policy.
Real-world scenario: A typical Coefficient of Variation case uses standard deviation 12 and mean 80. Enter the same figures below to reproduce the worked path.
What is Coefficient of Variation?
A scale-free dispersion metric useful when comparing variability across series with different units or means.
- Same units for SD and mean
- Mean ≠ 0
- Higher CV = more relative variability
The Formula
Worked Example
Common Use Cases
- Lab QA: assay variability
- Process control: relative spread
- Finance risk: return volatility vs mean
Pro Tips
- Prefer CV when means differ
- Watch signed means near zero
- State sample vs population SD
Limitations: Coefficient of Variation results are educational statistics aids—not formal statistical certification. Confirm assumptions (SRS, large-sample approximations, labeling) for your analysis.
FAQ
Sample or population SD?
Either—use the same definition your study reports. The formula structure is identical.
What if mean is 0?
CV is undefined—relative variation needs a non-zero mean.
Authoritative References
For statistical definitions and survey practice, consult: