Median Absolute Deviation in R (Example) | mad Function Explained
In this article, I’ll explain how to compute the median absolute deviation in the R programming language.
The tutorial is mainly relying on the mad R function. The basic R syntax and the definition of the mad function are as follows:
Basic R Syntax of mad:
Definition of mad:
In the following, I’ll show you an example code for the computation of the median absolute deviation in R.
Let’s jump right to it.
Example: Median Absolute Deviation in R (mad Function)
In this example, I’m going to use the following numeric vector as example input:
x <- c(3, 4, 1, 8, 2, 5, 2, 1) # Create example vector
Now, we can apply the mad R function in order to compute the median absolute deviation of this vector:
mad(x) # Apply mad function in R # 2.2239
As you can see based on the output in your RStudio console, the MAD of our example data is 2.2239.
Video & Further Resources
Below, you can find a video on the Statistics Globe YouTube channel where I describe the steps of this tutorial in expanded detail:
In the example above, I’ve shown you the basic application of the R mad function. However, there are several possibilities to modify the function. All options can be found in the R help documentation of mad:
Figure 1: R Help Documentation of mad() Function.
In case you need another example for the application of the mad function in R, you may also have a look at the following YouTube video of Mr. Math Expert
Furthermore, you might be interested to read some of the other R tutorials of this website:
- Standard Error in R
- Standard Deviation in R
- Variance in R
- Median in R
- R Functions List (+ Examples)
- The R Programming Language
To summarize: This R programming tutorial explained how to calculate the median absolute deviation. If you have any questions, please let me know in the comments below.