cv {goeveg} | R Documentation |

## Coefficient of variation (CV)

### Description

Compute the coefficient of variation (CV). The CV, also known as relative standard deviation (RSD), is a standardized measure of dispersion of a probability distribution or frequency distribution.
It is defined as the ratio of the standard deviation to the mean and is often expressed as a percentage.
In contrast to the standard deviation, it enables comparison between datasets as the CV is independent of the unit in which the measurement has been taken.
If `na.rm`

is `TRUE`

then missing values are removed before computation proceeds.

### Usage

```
cv(x, na.rm = FALSE)
```

### Arguments

`x` |
a numeric vector |

`na.rm` |
logical. Should missing values be removed? |

### Value

A numeric scalar – the sample coefficient of variation.

### Details

The coefficient of variation (CV) should be computed only for data measured on a ratio scale (i.e. data with an absolute zero). The CV may not have any meaning for data on an interval scale.

According to Dormann 2017 CV-values below 0.05 (5%) indicate very high precision of the data, values above 0.2 (20%) low precision. However, this is considered as a rule of thumb. In studies of highly variable systems (e.g. some ecological studies) CV values above 1 may occur.

The CV of a zero-length vector (after removal of `NA`

s if `na.rm = TRUE`

) is not defined and gives an error.
If there is only a single value, `sd`

is `NA`

and `cv`

returns `NA`

.

### References

Dormann, C. (2017). Parametrische Statistik. Verteilungen, maximum likelihood und GLM in R. *Springer*. doi:10.1007/978-3-662-54684-0

Frost, J. (2023). Coefficient of variation in statistics. Statistics by Jim. https://statisticsbyjim.com/basics/coefficient-variation/.

### See Also

### Examples

```
## Calculate CV for variable soil depth
cv(schedenenv$soil_depth)
```

*goeveg*version 0.7.4 Index]