Frequency Distribution Tool
Analyze data distribution with frequency tables and histograms.
Enter Your Data
Example Datasets:
π Summary Statistics
Count (n)
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Mean
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Median
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Mode
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Range:
Min:
Max:
Std Dev:
π Frequency Distribution Table
| Class/Value | Frequency (f) | Relative Freq | Percentage | Cumulative Freq | Cum. % |
|---|---|---|---|---|---|
| Total | 1.0000 | 100% | - | - |
π Histogram
π Text Histogram
How It Works
What is a Frequency Distribution?
A frequency distribution shows how often each value (or range of values) occurs in a dataset. It's one of the most fundamental ways to summarize and visualize data.
Types of Frequency Distributions
Discrete (Ungrouped)
For categorical or countable data with distinct values:
- Survey ratings (1, 2, 3, 4, 5)
- Number of children
- Shoe sizes
- Discrete counts
Example: Count how many times each exact value appears
Grouped (Class Intervals)
For continuous data or large ranges:
- Heights, weights
- Test scores (0-10, 11-20, etc.)
- Income ranges
- Ages (20-29, 30-39, etc.)
Example: Group data into bins/classes
Key Terms
- Frequency (f): Number of times a value/class occurs
- Relative Frequency: f / n (proportion as decimal)
- Percentage: Relative frequency Γ 100%
- Cumulative Frequency: Running total of frequencies
- Cumulative %: Running total of percentages
- Class Width: Range of values in each group
- Class Midpoint: Middle value of a class interval
Creating Grouped Frequency Distribution
- Determine number of classes: Typically 5-15 (Sturges' Rule: k β 1 + 3.322 logββ(n))
- Calculate class width: (Max - Min) / Number of classes
- Round up class width to convenient number
- Start with minimum or slightly below
- Create intervals: Non-overlapping, equal width
- Tally frequencies: Count data points in each class
Example: Discrete Distribution
Survey ratings: [3, 5, 4, 3, 5, 4, 5, 3, 4, 4]
| Rating | Frequency | Relative | % |
|---|---|---|---|
| 3 | 3 | 0.30 | 30% |
| 4 | 4 | 0.40 | 40% |
| 5 | 3 | 0.30 | 30% |
| Total | 10 | 1.00 | 100% |
Example: Grouped Distribution
Test scores: [67, 72, 85, 91, 78, 88, 95, 73, 81, 69]
| Class | Frequency | % | Cumulative % |
|---|---|---|---|
| 60-69 | 2 | 20% | 20% |
| 70-79 | 3 | 30% | 50% |
| 80-89 | 3 | 30% | 80% |
| 90-99 | 2 | 20% | 100% |
Histogram
A histogram is a graphical representation of a frequency distribution:
- X-axis: Values or class intervals
- Y-axis: Frequency (count or percentage)
- Bars touch (continuous data) or separated (discrete)
- Bar height represents frequency
Distribution Shapes
- Normal (Bell-shaped): Symmetric, most common
- Skewed Right: Long tail to the right
- Skewed Left: Long tail to the left
- Uniform: All frequencies roughly equal
- Bimodal: Two peaks
- Multimodal: Multiple peaks
Applications
- Education: Grade distributions, test score analysis
- Business: Sales patterns, customer demographics
- Healthcare: Patient age distributions, treatment outcomes
- Quality Control: Defect rates, measurement distributions
- Social Science: Survey response patterns
- Economics: Income distribution, price ranges
Choosing Number of Classes
- Sturges' Rule: k = 1 + 3.322 logββ(n)
- Square Root Rule: k = βn
- Rice Rule: k = 2n^(1/3)
- Practical: Use 5-15 classes depending on data
Embed This Util
You can embed this util on your own site as a widget. Adding ?embed=1 to the URL loads a compact
version with just the tool itself; no header, menu, or documentation. Paste this snippet into your HTML:
Copy snippet
Adjust the height to taste.
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