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A graphical display of the distribution of numerical data using adjacent bars whose areas represent frequencies within bins.
DESCRIPTION
Histograms summarize distributions by grouping numeric values into bins and plotting their frequencies. They reveal modality, skewness, spread, and outliers. Bin width selection is critical; rules include Scott’s, Freedman–Diaconis, and Sturges. Overly wide bins obscure detail, while narrow bins add noise. Histograms support EDA, quality control, and performance monitoring. They are unsuitable for small samples where KDEs or dot plots may be clearer.
ALTERNATIVE DEFINITIONS
Wikipedia
A histogram is an approximate representation of the distribution of numerical data.
Highlights approximation to an underlying distribution.
Wolfram MathWorld
A histogram is a graph that displays a frequency distribution.
Emphasizes frequency distribution visualization.
RELATED TERMS
Frequency Distribution Probability Density Function Bar Chart Cumulative Distribution Function Box Plot Q-Q Plot Binning Data Anomaly Detection Empirical Distribution
COMPETING TERMS
KNOWLEDGE AREAS
Data Visualization Data Science Mathematics
TARGET AUDIENCE
Data Analyst BI Specialist Data Scientist
EXTERNAL SOURCES
- Wikipedia - Histogram
- Matplotlib - Histogram plotting API in Python
- ggplot2 - R histogram layer documentation
- NIST/SEMATECH - NIST guidance on histograms
TOP QUESTIONS
How do I choose bin width for a Histogram?
Use rules like Freedman–Diaconis, Scott’s, or Sturges, and validate visually. Adaptive binning can capture variable density.
Category: Best Practice
What’s the difference between a Histogram and a bar chart?
Histograms display continuous numeric distributions with adjacent bins; bar charts show categorical counts with separated bars.
Category: Misunderstanding
When should I prefer KDE over a Histogram?
For smooth density estimates, particularly with moderate sample sizes, KDE may reveal structure obscured by binning.
Category: Comparison
How can Histograms mislead?
Poor binning or truncated ranges can hide multimodality or create false patterns. Always disclose binning and axis limits.
Category: Risk
How to compare two distributions with Histograms?
Use overlaid semi-transparent histograms or faceted small multiples. Ensure consistent binning and scaling.
Category: Design
Can Histograms handle weighted data?
Yes, many plotting libraries support weights so bar areas reflect weighted frequencies or probabilities.
Category: Technique
What sample size is needed for a meaningful Histogram?
There’s no strict threshold, but very small samples can produce misleading shapes. Consider dot plots for n < 30.
Category: Requirements
How to detect outliers using a Histogram?
Look for isolated bins far from the main mass. Complement with box plots and robust statistics.
Category: Usage
How do normalized Histograms relate to PDFs?
Normalizing by total count and bin width approximates the underlying probability density function.
Category: Concept