# Why & How to Set a Random Seed in R (Example) | set.seed Function Explained

In this R programming tutorial you’ll learn how to **specify a random seed using the set.seed() function**.

Table of contents:

Let’s start right away…

## Reasons for Using a Random Seed in R

A random seed (or seed state) is a number that initializes a pseudorandom number generator.

Pseudorandom numbers are not truly random, but they aim to be as patternless as possible to simulate randomness.

Why is this important when using the R programming language?

In R, we can set a random seed to make the output of our R code reproducible. By setting a specific seed, the random processes in our script always start at the same point and hence lead to the same result.

Let’s do this in practice…

## Example: Setting Random Seed Using set.seed() Function in R

In this example, I’ll show what happens if you don’t use a random seed and how you can use the set.seed function to set a seed in R.

First, let’s generate some random numbers in R using the rpois function:

rpois(5, 3) # Generate random numbers without seed # [1] 1 3 3 2 6 |

rpois(5, 3) # Generate random numbers without seed # [1] 1 3 3 2 6

The output of the previous R syntax is a numeric vector with the elements 1, 3, 3, 2, and 6.

Let’s execute exactly the same R code again:

rpois(5, 3) # Generate random numbers again #[1] 3 6 3 1 2 |

rpois(5, 3) # Generate random numbers again #[1] 3 6 3 1 2

Now, the result is a numeric vector consisting of the vector elements 3, 6, 3, 1, and 2.

As you can see, the output is completely different even though we have used exactly the same R code.

This can make it impossible to replicate a specific output and that makes it difficult to retrace the steps the programmer of the R code has made.

For that reason, it is considered as best practice for researchers to set a random seed at the beginning of R scripts that involve random processes.

Let’s see how we can do that in R!

The basic installation of the R programming language provides the set.seed function. Within the set.seed function, we simply have to specify a numeric value to set a seed.

Have a look at the following R code:

set.seed(12345) # Set seed for reproducibility rpois(5, 3) # Generate random numbers with seed # [1] 4 5 4 5 3 |

set.seed(12345) # Set seed for reproducibility rpois(5, 3) # Generate random numbers with seed # [1] 4 5 4 5 3

We generated the random sequence 4, 5, 4, 5, and 3.

Let’s do this again with the same seed as before:

set.seed(12345) # Set same random seed rpois(5, 3) # Generate random numbers with same seed # [1] 4 5 4 5 3 |

set.seed(12345) # Set same random seed rpois(5, 3) # Generate random numbers with same seed # [1] 4 5 4 5 3

The output is exactly the same – great!

## Video & Further Resources

In case you need more information on the topics of this tutorial, you might want to watch the following video of my YouTube channel. I’m illustrating the R programming code of this tutorial in the video:

*The YouTube video will be added soon.*

Furthermore, you might read the related posts on this homepage:

Summary: At this point you should have learned how to **apply the set.seed function** in the R programming language. Let me know in the comments section below, if you have additional questions.

**5**/

**5**(

**1**vote )

### Subscribe to my free statistics newsletter: