 # Title: Master R Notebooks and Random Number Generation

### Introduction to R Notebooks

Welcome back to another exciting installment in our R programming series! In this blog post, we will explore R Notebooks and dive deeper into generating random numbers in R. If you haven’t already, check out our YouTube channel, Cradle To Graver, for more informative tutorials.

## Recommended Books

To further enhance your understanding of R programming and data manipulation, we recommend the following books (as an Amazon Associate, I may earn a small commission from these links):

### Getting Started with R Notebooks

To create a new R Notebook, follow these steps:

1. Open RStudio
2. Click on “File”
3. Select “New File”
4. Choose “R Notebook”

Now that you have created a new R Notebook, let’s begin by adding some essential elements:

• Headings: Use the pound symbol (#) followed by a space to create headings in markdown cells. For example: `# Random Number Generator`
• Code chunks: To insert a code chunk, press `Ctrl + Option + I` (Mac) or `Ctrl + Alt + I` (Windows). Name your code chunks for better organization, like so: ` `{r random_number_chunk}`
• Bullet points: To create bullet points in markdown cells, start a line with an asterisk (*) followed by a space. For example: `* Item 1`

## Recommended Books

To further enhance your understanding of R programming and data manipulation, we recommend the following books (as an Amazon Associate, I may earn a small commission from these links):

### Random Number Generation in R

In R, there are two main functions to generate random numbers:

1. `runif()`: Generates random numbers with decimal places between specified minimum and maximum values
2. `sample()`: Generates random integers by taking a sample of numbers from a specified pool

To generate random numbers with `runif()`, use the following syntax:

``runif(n, min, max)``
• `n`: The number of random numbers you want to generate
• `min`: The minimum value (default is 0)
• `max`: The maximum value (default is 1)

For example, to generate 10 random numbers between 10 and 40:

``runif(10, 10, 40)``

To generate random integers with `sample()`, use the following syntax:

``sample(x, size, replace = FALSE)``
• `x`: A vector of numbers to sample from
• `size`: The number of items to choose from the vector `x`
• `replace`: Whether sampling should be with replacement (default is `FALSE`)

For example, to generate 10 random integers between 10 and 40:

``sample(10:40, 10)``

### Using Seeds for Reproducible Random Numbers

In data analysis, generating random numbers that can be reproduced is often necessary. To achieve this, R provides the `set.seed()` function, which initializes the random number generator with a specified seed value.

To set a seed, call the `set.seed()` function with a specific integer:

``set.seed(345)``

Any random numbers generated after setting the seed will be the same every time you run the code, making your results reproducible.

### Clearing and Removing Variables in R

There might be instances where you want to remove specific variables from your environment. To do this, you can use the `rm()` function:

``rm(variable_name)``

Alternatively, you can use the “broom” icon in the Environment pane to clear all variables simultaneously.