Consider any dataset, sort its entries from smallest to largest and split the resulting list in 4 equal subsets. The **quartiles** are the values of the dataset that cut it off in 4.

Quartiles are called:

**Q1**: the first quartile under which the first 25% of the data in the set can be found,**Q2**: the second quartile under which the first 50% of the data in the set can be found (by the way, Q2 is also the median),**Q3**: the third quartile under which the first 75% of the data in the set can be found.

In addition, one also refers to:

**Q0**as the minimum value in the set,**Q4**as the maximum value in the set.

For info, note that the set of data between Q1 and Q3 (which contains the middle 50% of the data) is the **interquartile range (IQR)**.

In R, quartiles may be obtained using the function `quantile()`

(NB: this is not a typo, it is quaNtile and not quaRtile, there is a good explanation for it, believe meβ¦). If you choose to use only `quantile()`

with no other argument than the vector containing the dataset, R returns Q0, Q1, Q2, Q3, Q4 and Q5:

```
my.dataset <- c(1,2,3,4,5,6,7,8,9,10)
quantile(my.dataset)
```

```
## 0% 25% 50% 75% 100%
## 1.00 3.25 5.50 7.75 10.00
```

If you only need Q1, Q2 and Q3, say it using decimals as follows:

`quantile(my.dataset, c(0.25, 0.5, 0.75))`

```
## 25% 50% 75%
## 3.25 5.50 7.75
```