Creating a Box Plot in R
Before finding the range, let’s create a box plot. Consider a simple example with a set of data.
# Create a sample vector of data
data <- c(1, 2, 2, 3, 4, 5, 6, 6, 7, 8, 9, 10, 12, 14, 15, 18, 20, 22)
# Create a box plot
boxplot(data, main = "Box Plot Example", xlab = "Sample Data")
Output:
This code snippet creates a box plot with the default whisker range, usually 1.5 times the interquartile range (IQR) from the quartiles.
Finding the Range of a Box Plot
To find the range of a box plot, you need to identify the five-number summary, which includes:
- Minimum: The smallest value not considered an outlier.
- First Quartile (Q1): The 25th percentile of the data.
- Median (Q2): The 50th percentile (middle value) of the data.
- Third Quartile (Q3): The 75th percentile of the data.
- Maximum: The largest value not considered an outlier.
You can extract these values and determine the whisker range using the boxplot.stats function in R:
# Get the box plot statistics
box_stats <- boxplot.stats(data)
# Display the five-number summary
print(box_stats$stats)
Output:
[1] 1.0 4.0 7.5 14.0 22.0
Whisker Range
The whiskers in a box plot typically extend to 1.5 times the IQR from the quartiles. You can calculate this range to find the typical minimum and maximum values for the box plot:
# Calculate the interquartile range (IQR)
iqr <- box_stats$stats[4] - box_stats$stats[2]
# Calculate the lower whisker
lower_whisker <- box_stats$stats[2] - 1.5 * iqr
# Calculate the upper whisker
upper_whisker <- box_stats$stats[4] + 1.5 * iqr
cat("Lower whisker:", lower_whisker, "\n")
cat("Upper whisker:", upper_whisker, "\n")
Output:
Lower whisker: -11
Upper whisker: 29
In addition to the whiskers, box plots can also display outliers. Outliers are data points outside the whisker range. To find these, you can use the out attribute from boxplot.stats:
# Get the outliers
outliers <- box_stats$out
print(outliers)
Output:
numeric(0)
Find Range of Box Plot in R
A box plot (box-and-whisker plot) is a visualization used to depict the distribution of data based on a five-number summary: minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum. The box plot provides insights into data distribution, central tendency, variability, and outliers.
Understanding how to find the range of a box plot involves identifying the whiskers’ endpoints, which typically represent the range of non-outlier data, and calculating the interquartile range (IQR). This guide explores how to determine these values in R Programming Language.