R allows for installation and use of toolboxes (called packages) made by third parties. Such packages are often useful for specific types of analyses and provide multitudes of functions and possibilities. With regards to descriptive statistics, the package `**pastecs**`

is one of these toolboxes. Note that such a package must be installed/activated in R prior to analyzing data. NB: if `pastecs`

is not installed yet, simply use the following code:

`install.packages("pastecs")`

```
## Installing package into 'C:/Program Files/R/library'
## (as 'lib' is unspecified)
```

```
## package 'pastecs' successfully unpacked and MD5 sums checked
##
## The downloaded binary packages are in
## C:\Users\femjs\AppData\Local\Temp\Rtmp6VY48c\downloaded_packages
```

Once the package has been installed, you will need to activate it **everytime you restart R/Rstudio**. Use this line of code:

`library(pastecs)`

`Pastecs`

contains a multitude of functions, among which `stat.desc()`

. Running `stat.desc()`

on a dataset returns a list of useful parameters such as number of values, number of null values, number of missing values, minimum, maximum, range, median, mean, standard error of the mean, standard deviation, variance and more. Let’s use `stat.desc()`

on the following example:

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

```
## nbr.val nbr.null nbr.na min max
## 10.0000000 0.0000000 0.0000000 1.0000000 10.0000000
## range sum median mean SE.mean
## 9.0000000 55.0000000 5.5000000 5.5000000 0.9574271
## CI.mean.0.95 var std.dev coef.var
## 2.1658506 9.1666667 3.0276504 0.5504819
```

`stat.desc()`

is one of many functions included in `pastecs`

. You may find more info and learn about all the possibilities given by the package by clicking here.

Sadly, `stat.desc()`

displays values using a scientific notation which does not look so attractive to the reader. It is possible to use the command `options()`

to simplify the display. Note that you have to use the command `options()`

**prior** to running `stat.desc()`

:

```
options(scipen=100)
options(digits=2)
my.dataset <- c(1,2,3,4,5,6,7,8,9,10)
stat.desc(my.dataset)
```

```
## nbr.val nbr.null nbr.na min max
## 10.00 0.00 0.00 1.00 10.00
## range sum median mean SE.mean
## 9.00 55.00 5.50 5.50 0.96
## CI.mean.0.95 var std.dev coef.var
## 2.17 9.17 3.03 0.55
```