# Coefficient of Variation Calculator

Determine coefficients of variation accurately with our Coefficient of Variation Calculator.

 Enter Inputs 5,20,40,80,100Enter the Numbers with Comma separated(,)
 Result: No.of Inputs Mean Standard Deviation(SD) Variance Coefficient(CV)

## Similar Calculators:

The coefficient of variation (CV) is a statistical measure used to assess the relative variability or risk associated with a data set. It's often expressed as a percentage and is calculated by dividing the standard deviation (σ) of a dataset by its mean (average) value (μ) and then multiplying by 100. The formula for calculating the coefficient of variation is:

CV = (σ / μ) * 100%

## How to Calculate the Coefficient of Variation

### Step 1: Gather Data

Obtain the dataset for which you want to calculate the coefficient of variation. This data can represent various metrics, such as stock returns, investment risks, or any other variable you want to evaluate for variability.

### Step 2: Calculate the Mean

Find the mean (average) value of the dataset (μ) by adding up all the data points and dividing by the total number of data points.

### Step 3: Calculate the Standard Deviation

Compute the standard deviation (σ) of the dataset. The standard deviation measures the amount of variation or dispersion in the data points. It's often calculated using statistical software or spreadsheet tools.

### Step 4: Calculate the Coefficient of Variation

Apply the formula for the coefficient of variation: CV = (σ / μ) * 100%. This formula yields the CV as a percentage, allowing you to assess the relative variability or risk of the data.

### Step 5: Interpret the Result

The coefficient of variation is a valuable tool for comparing the risk or variability of different datasets, especially when dealing with data of different units or scales. A higher CV indicates higher relative variability, while a lower CV suggests lower relative variability. By comparing the CVs of different datasets, you can make more informed decisions in fields such as finance, investments, quality control, or research.