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A **coefficient of variation**, often abbreviated as CV, is a way to measure how spread out values are in a dataset relative to the mean. It is calculated as:

**CV** =Â Ïƒ /Â Î¼

where:

Ïƒ = standard deviation of dataset

Î¼ = mean of dataset

In its simplest terms, the coefficient of variation is simply the ratio between the standard deviation and the mean.

**When is the Coefficient of Variation Used?**

The coefficient of variation is often used to compare the variation between two different datasets.

In the real world, itâ€™s often used in finance to compare the mean expected return of an investment relative to the expected standard deviation of the investment. This allows investors to compare the risk-return trade-off between investments.

For example, suppose an investor is considering investing in the following two mutual funds:

Mutual Fund A: mean = 7%, standard deviationÂ = 12.4%

Mutual Fund B: mean = 5%, standard deviationÂ = 8.2%

Upon calculating the coefficient of variation for each fund, the investor finds:

CV for Mutual Fund A = 12.4% / 7% =Â **1.77**

CV for Mutual Fund B = 8.2% / 5% =Â **1.64**

Since Mutual Fund B has a lower coefficient of variation, it offers a better mean return relative to the standard deviation.

**How to Calculate the Coefficient of Variation in Excel**

There is no built-in formula in Excel to calculate the coefficient of variation for a dataset, but fortunately itâ€™s relatively easy to calculate using a couple simple formulas. The following example illustrates how to calculate the coefficient of variation for a given dataset.

Suppose we have the following dataset that contains the exam scores of 20 students:

To calculate the coefficient of variation for this dataset, we only need to know two numbers: the mean and the standard deviation. These can be calculated using the following formulas:

Mean: **=AVERAGE(A2:A21)**

Standard deviation: **=STDEV(A2:A21)**

To calculate the coefficient of variation, we then divide the standard deviation by the mean:

The coefficient of variation turns out to beÂ **0.0864**.

Note that we also could have used just one formula to calculate the CV:

This results in the same CV ofÂ **0.0864**.