This calculator helps you analyze the distribution of your data through its key percentiles. It calculates the minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum values, providing a comprehensive overview of your dataset's spread and central tendency. The calculator also generates both a professional box plot and an annotated histogram to visualize your data's distribution, automatically detects and highlights outliers, and provides detailed interpretation explaining whether your data is symmetric or skewed.
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Understanding the Five-Number Summary
Definition
The Five-Number Summary provides a comprehensive overview of a dataset's distribution through five key values: minimum, first quartile (Q1), median (Q2), third quartile (Q3), and maximum.
Components
- Minimum (): Smallest value in the dataset
- First Quartile (): 25th percentile
- Median (): 50th percentile
- Third Quartile (): 75th percentile
- Maximum (): Largest value in the dataset
Key Metrics
Range:
Interquartile Range (IQR):
Important Considerations
- Not sensitive to the exact values of outliers
- May not fully capture multimodal distributions
- Should be used alongside other descriptive statistics
Practical Example with Box Plot
Understanding Five-Number Summary Through Box Plots
Consider a dataset of student test scores. Here's how to read the five-number summary from a box plot:
Five-Number Summary
- Minimum: 10 points
- Q1: 15 points (25th percentile)
- Median: 20 points (50th percentile)
- Q3: 25 points (75th percentile)
- Maximum: 30 points
Box Plot Components
- The box spans from Q1 to Q3
- The line inside the box shows the median
- The whiskers extend to min and max values
- Points beyond whiskers represent outliers
- The IQR is the height of the box (Q3 - Q1 = 10 points)
Interpretation
- • The middle 50% of students scored between 15 and 25 points
- • The median score of 20 points indicates typical performance
- • The distribution is symmetric (median in center of box)
- • Two outliers exist at 8 and 32 points
- • The total range (excluding outliers) is 20 points
Creating Your Own Box Plot
To create a box plot from your data:
- Arrange your data in ascending order
- Find the median (Q2) by locating the middle value
- Find Q1 (median of lower half) and Q3 (median of upper half)
- Calculate the IQR (Q3 - Q1)
- Identify outliers (values beyond Q1 - 1.5×IQR or Q3 + 1.5×IQR)
- Draw the box spanning Q1 to Q3 with a line at the median
- Add whiskers extending to the min/max (excluding outliers)
- Plot any outliers as individual points
You can use our Box Plot Calculator to create box plots automatically from your data.
How to calculate Five Number Summary in R
Use summary() for basic statistics orquantile() for more control over percentiles.
# Sample numerical data
data <- c(12, 15, 18, 20, 22, 25, 28, 30, 35, 40, 45, 50, 55, 60, 65)
# Method 1: Quick summary (includes mean and other stats)
summary(data)
# Method 2: Exact five number summary
five_num <- quantile(data, probs = c(0, 0.25, 0.5, 0.75, 1))
names(five_num) <- c("Minimum", "Q1", "Median", "Q3", "Maximum")
print(five_num)
# Method 3: Detailed analysis with additional statistics
library(tidyverse)
five_number_summary <- tibble(
Statistic = c("Minimum", "Q1", "Median", "Q3", "Maximum", "Range", "IQR"),
Value = c(
min(data),
quantile(data, 0.25),
median(data),
quantile(data, 0.75),
max(data),
max(data) - min(data),
IQR(data)
)
)
print(five_number_summary)
# Visualization: Box plot
boxplot(data,
main = "Five Number Summary Box Plot",
ylab = "Values",
col = "lightblue",
border = "darkblue")
# Add labels to the box plot
text(1.3, quantile(data, c(0, 0.25, 0.5, 0.75, 1)),
labels = c("Min", "Q1", "Median", "Q3", "Max"),
cex = 0.8)
How to calculate Five Number Summary in Python
Use describe() method in pandas or numpy.percentile() for precise control.
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
# Sample data
data = [12, 15, 18, 20, 22, 25, 28, 30, 35, 40, 45, 50, 55, 60, 65]
df = pd.DataFrame({'values': data})
# Method 1: Using pandas describe (includes additional stats)
print("Pandas describe():")
print(df['values'].describe())
# Method 2: Manual calculation of five number summary
five_number = {
'Minimum': np.min(data),
'Q1': np.percentile(data, 25),
'Median': np.median(data),
'Q3': np.percentile(data, 75),
'Maximum': np.max(data)
}
# Additional statistics
five_number['Range'] = five_number['Maximum'] - five_number['Minimum']
five_number['IQR'] = five_number['Q3'] - five_number['Q1']
# Display as DataFrame
summary_df = pd.DataFrame(list(five_number.items()),
columns=['Statistic', 'Value'])
print("\nFive Number Summary:")
print(summary_df)
# Method 3: Using numpy quantile for exact percentiles
percentiles = np.percentile(data, [0, 25, 50, 75, 100])
labels = ['Minimum', 'Q1', 'Median', 'Q3', 'Maximum']
for label, value in zip(labels, percentiles):
print(f"{label}: {value}")
# Visualization: Box plot
plt.figure(figsize=(8, 6))
plt.boxplot(data, tick_labels=['Data'])
plt.title('Five Number Summary Box Plot')
plt.ylabel('Values')
plt.grid(True, alpha=0.3)
plt.show()
# Histogram with quartile lines
plt.figure(figsize=(10, 6))
plt.hist(data, bins=10, alpha=0.7, color='lightblue', edgecolor='black')
for i, (label, value) in enumerate(zip(labels, percentiles)):
color = ['red', 'orange', 'green', 'orange', 'red'][i]
plt.axvline(value, color=color, linestyle='--', linewidth=2, label=label)
plt.xlabel('Values')
plt.ylabel('Frequency')
plt.title('Distribution with Five Number Summary')
plt.legend()
plt.grid(True, alpha=0.3)
plt.show()
How to calculate Five Number Summary in Excel
Use MIN, QUARTILE, and MAX functions, or create a box plot for visualization.
=MIN(A1:A100) # Minimum
=QUARTILE(A1:A100,1) # Q1 (First Quartile)
=MEDIAN(A1:A100) # Q2 (Median)
=QUARTILE(A1:A100,3) # Q3 (Third Quartile)
=MAX(A1:A100) # Maximum
=MAX(A1:A100)-MIN(A1:A100) # Range
=QUARTILE(A1:A100,3)-QUARTILE(A1:A100,1) # IQR
Method 1: Using Formulas
=MIN(A1:A100) - Find the minimum value
=QUARTILE(A1:A100,1) - Calculate Q1 (25th percentile)
=MEDIAN(A1:A100) - Find the median (Q2)
=QUARTILE(A1:A100,3) - Calculate Q3 (75th percentile)
=MAX(A1:A100) - Find the maximum value
Method 2: Data Analysis ToolPak
- Go to Data → Data Analysis
- Select Descriptive Statistics
- Choose your data range
- Check Summary statistics
- Click OK to get comprehensive statistics including quartiles
Method 3: Box Plot Visualization
- Select your data range
- Go to Insert → Charts → Statistical → Box and Whisker
- Excel will automatically create a box plot showing your five number summary
- The box shows Q1, median, and Q3; whiskers show min and max