Coefficient of Variation Calculator

Coefficient of Variation is evaluated from Input method, Mean and Std Dev. The calculation reports Mean, Standard Deviation and Coefficient of Variation.

Results

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About the Coefficient of Variation Calculator

Coefficient of Variation is treated here as a quantitative relation between Input method, Mean, Std Dev and Number 1 and Mean, Standard Deviation and Coefficient of Variation.

The calculator uses a multi formula configuration. Each reported value is read as a direct evaluation of the stored rules with the declared field formats and units.

Formula basis:
CV = (standard deviation / mean) x 100%

Interpret the outputs in the order shown by the result fields. Optional inputs affect only the outputs that depend on those variables.

Formula & How It Works

The calculation applies the following relations exactly as recorded in the metadata:

CV = (standard deviation / mean) x 100%

Each output field is produced by substituting the supplied inputs into the relevant relation and then applying the declared rounding or text format.

Worked Examples

Example 1: Comparing two investments: Stock A (mean 12%, SD 3%) vs. Stock B (mean 8%, SD 1.5%)

Inputs

input_mode: params mean_in: 12 sd_in: 3
Mean: 12. Standard Deviation: 3. Coefficient of Variation: 25%

With Input method = params, Mean = 12 and Std Dev = 3 as the stated inputs, the result is Mean = 12, Standard Deviation = 3 and Coefficient of Variation = 25%. Each value corresponds to the declared output fields.

Example 2: Lab test precision: Glucose measurements (mg/dL): 98, 101, 99, 102, 100, 103, 97, 100

Inputs

input_mode: raw n1: 98 n2: 101 n3: 99 n4: 102 n5: 100 n6: 103 n7: 97 n8: 100
Mean: 82. Standard Deviation: 37.9883. Coefficient of Variation: 46.33%

With Input method = raw, Number 1 = 98, Number 2 = 101 and Number 3 = 99 as the stated inputs, the result is Mean = 82, Standard Deviation = 37.9883 and Coefficient of Variation = 46.33%. Each value corresponds to the declared output fields.

Example 3: Manufacturing quality: Part A (mean 50mm, SD 0.5mm) vs. Part B (mean 10mm, SD 0.3mm)

Inputs

input_mode: params mean_in: 50 sd_in: 0.5
Mean: 50. Standard Deviation: 0.5. Coefficient of Variation: 1%

With Input method = params, Mean = 50 and Std Dev = 0.5 as the stated inputs, the result is Mean = 50, Standard Deviation = 0.5 and Coefficient of Variation = 1%. Each value corresponds to the declared output fields.

Example 4: City rainfall data (inches/month): 2.1, 3.4, 1.8, 4.2, 5.1, 0.9, 1.2, 3.8, 2.7, 4.5

Inputs

input_mode: raw n1: 2.1 n2: 3.4 n3: 1.8 n4: 4.2 n5: 5.1 n6: 0.9 n7: 1.2 n8: 3.8 n9: 2.7 n10: 4.5
Mean: 2.97. Standard Deviation: 1.4484. Coefficient of Variation: 48.77%

With Input method = raw, Number 1 = 2.1, Number 2 = 3.4 and Number 3 = 1.8 as the stated inputs, the result is Mean = 2.97, Standard Deviation = 1.4484 and Coefficient of Variation = 48.77%. Each value corresponds to the declared output fields.

Common Use Cases

  • Compare variability between datasets with different means
  • Assess consistency in quality control
  • Evaluate investment risk relative to return