# 1. Introduction

Boxplots, also known as whisker plots, are visual representations of the distribution of a dataset. They highlight the median, quartiles, and potential outliers. Boxplots provide a compact view of the data's range and its variability. In this guide, we'll understand how to create a boxplot using R.

# 2. Program Overview

The program will:

1. Create a numeric dataset.

2. Use the boxplot() function from base R to generate and display a boxplot.

3. Customize the appearance of the boxplot.

# 3. Code Program

``````# Create a numeric dataset
data <- c(12, 15, 13, 20, 22, 25, 27, 30, 10, 14, 16, 19, 21, 26, 29)

# Generate and display a boxplot with main title and axis labels
boxplot(data,
main = "Boxplot of Data",
ylab = "Value",
col = "lightgreen",
border = "black")

``````

### Output:

```[A boxplot will be displayed with the title "Boxplot of Data". The y-axis is labeled "Value". The box is colored light green with a black border.]
```

# 4. Step By Step Explanation

1. We initiate by creating a numeric dataset named "data". This dataset contains 15 numeric values. For this instance, we are using a fictional dataset.

2. The boxplot() function is utilized to create the boxplot. We supply it with several parameters:

- The first parameter is our dataset, "data".- The "main" parameter sets the title of the boxplot.

- "ylab" is used to label the y-axis.- The "col" parameter determines the color of the box, which is set to light green in this case.

- The "border" parameter sets the color of the box's borders. We use black for visibility.

3. Upon executing the code, R will present a boxplot in a separate graphical window. This boxplot showcases the data's median, quartiles, and potential outliers, offering a compact overview of the data distribution.

Remember: The exact visuals of the boxplot can differ based on your R graphical settings and the specific data used.