# What is a Box Plot and How to Read It

A Box Plot is a convenient way of graphically depicting groups of numerical data through their quartiles. They provide a graphical rendition of statistical data based on the minimum, first quartile, median, third quartile, and maximum, also Outliers can be plotted as individual points.

The term "box plot" comes from the fact that the graph looks like a rectangle with lines extending from the top and bottom. Because of the extending lines, this type of graph is sometimes called a box-and-whisker plot. The distances between the different box parts represent the degree of a data dispersion and a data asymmetry to identify outliers. The points values can be compared between themselves (single-series chart) or values inside the category (multi-series chart). In case of several series points are grouped by categories.

### Interpreting a Box Plot

The box plot is interpretted as follows:

- The box itself contains the middle 50% of the data. The upper edge (hinge) of the box indicates the 75th percentile of the data set, and the lower hinge indicates the 25th percentile. The range of the middle two quartiles is known as the inter-quartile range.
- The line in the box indicates the median value of the data.
- If the median line within the box is not equidistant from the hinges, then the data is skewed.
- The ends of the vertical lines or "whiskers" indicate the minimum and maximum data values, unless outliers are present in which case the whiskers extend to a maximum of 1.5 times the inter-quartile range.
- The points outside the ends of the whiskers are outliers or suspected outliers.

#### Course Downloads

- Overview of Data Visualization
- When to Use Bar Chart, Column Chart, and Area Chart
- What is Line Chart and When to Use It
- What are Pie Chart and Donut Chart and When to Use Them
- How to Read Scatter Chart and Bubble Chart
- What is a Box Plot and How to Read It
- Understanding Japanese Candlestick Charts and OHLC Charts
- Understanding Treemap, Heatmap and Other Map Charts
- Visualization in Data Science
- Graphic Systems in R
- Accessing Built-in Datasets in R
- How to Create a Scatter Plot in R
- Create a Scatter Plot in R with Multiple Groups
- Creating a Bar Chart in R
- Creating a Line Chart in R
- Plotting Multiple Datasets on One Chart in R
- Adding Details and Features to R Plots
- Introduction to ggplot2
- Grammar of Graphics in ggplot
- Data Import and Basic Manipulation in R - German Credit Dataset
- Create ggplot Graph with German Credit Data in R
- Splitting Plots with Facets in ggplots
- ggplot2 - Chart Aesthetics and Position Adjustments in R
- Creating a Line Chart in ggplot 2 in R
- Add a Statistical Layer on Line Chart in ggplot2
- stat_summary for Statistical Summary in ggplot2 R
- Facets for ggplot2 Charts in R (Faceting Layer)
- Coordinates in ggplot2 in R
- Changing Themes (Look and Feel) in ggplot2 in R

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