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# How to Calculate Median Absolute Deviation in R

The median absolute deviation measures the spread of observations in a dataset.

Itâ€™s a particularly useful metric because itâ€™s less affected by outliers than other measures of dispersion like standard deviation and variance.

The formula to calculate median absolute deviation, often abbreviated MAD, is as follows:

where:

• xi: The ith value in the dataset
• xm: The median value in the dataset

The following examples shows how to calculate the median absolute deviation in R by using the built-inÂ mad() function.

### Example 1: Calculate MAD for a Vector

The following code shows how to calculate the median absolute deviation for a single vector in R:

```#define data

[1] 11.1195
```

The median absolute deviation for the dataset turns out to beÂ 11.1195.

### Example 2: Calculate MAD for a Column in a Data Frame

The following code shows how to calculate MAD for a single column in a data frame:

```#define data
data #calculate MAD for column y in data frame

[1] 2.9652
```

The median absolute deviation for column y turns out to be 2.9652.

### Example 3: Calculate MAD for Multiple Columns in a Data Frame

The following code shows how to calculate MAD for multiple columns in a data frame by using theÂ sapply() function:

```#define data
data

#calculate MAD for all columns in data frame