Coefficient of Variation Calculator
Compare relative variability between data sets with different units or scales.
What the Coefficient of Variation Calculator does
The coefficient of variation expresses standard deviation as a percentage of the mean. Because it is unitless, it lets you compare the consistency of measurements taken in completely different units — say rainfall in millimetres against temperature in degrees.
Formula
CV = (Standard deviation ÷ |Mean|) × 100
Inputs explained
| Input | Unit | Required | Notes |
|---|---|---|---|
| Input method | one of 2 options | Yes | — |
| Data set | text | In some modes | Separate values with commas, spaces or new lines. Shown Input method is Raw data. |
| Mean | number | In some modes | Shown Input method is Mean and standard deviation. |
| Standard deviation | number | In some modes | Accepts 0 or more. Shown Input method is Mean and standard deviation. |
| Data set type | one of 2 options | Yes | — |
How to use it
- Choose Input method and Data set type.
- Fill in the remaining inputs the form shows for your choice.
- Select Calculate.
Worked example
A process with a mean of 250 and a standard deviation of 18.
- Mean
- 250
- SD
- 18
18 ÷ 250 × 100 = 7.2% — low variability, a consistent process.
Reading the result
- "As a ratio" is the same information as CV on a 0–1 scale rather than a percentage — useful when a formula elsewhere expects the ratio form.
- Comparing CV against the low/moderate/high/very-high bands only makes sense within a similar context — the FAQ notes labs often want under 15% while financial returns routinely exceed 100%, so a "high variability" verdict is relative to a generic threshold, not universal.
Assumptions and limitations
- CV assumes a ratio-scale variable with a meaningful, non-arbitrary zero — the notes flag Celsius as the classic failure case, so any interval-scale measurement with an arbitrary zero produces a technically-computed but meaningless number.
Common mistakes
- Comparing CV between a small sample and a much larger one as if the precision behind each figure were equal — CV itself carries no information about how reliably it was estimated.
Frequently asked questions
When is CV not appropriate?
When the data can take negative values or the mean sits near zero. Temperature in Celsius is the classic failure case — the ratio becomes meaningless around freezing.
What counts as a good CV?
It is context-dependent. Laboratory assays often require under 15%; financial returns routinely exceed 100%.