Key Facts
- Category
- Data Analysis
- Input Types
- textarea, select, number, text, checkbox
- Output Type
- text
- Sample Coverage
- 4
- API Ready
- Yes
Overview
The Number Range Statistics tool allows you to quickly analyze datasets by grouping numbers into specific intervals, providing clear insights into frequency distribution and data patterns.
When to Use
- •When you need to create a histogram or frequency distribution from a raw list of numbers.
- •When you want to categorize large datasets into meaningful buckets like age groups, price ranges, or test scores.
- •When you need to verify data density across specific numerical segments for reporting or research.
How It Works
- •Paste your list of numbers into the input field, selecting the appropriate separator format.
- •Choose a range type, such as equal width, fixed interval, or custom ranges, to define how your data is segmented.
- •Configure optional settings like bin counts or specific start and end values to refine your analysis.
- •Generate the results in your preferred format, including summary statistics and chart-ready data.
Use Cases
Analyzing student test score distributions to determine grade brackets.
Grouping customer purchase amounts into price tiers for marketing analysis.
Categorizing sensor readings into safety thresholds for quality control reports.
Examples
1. Analyzing Test Score Distribution
Teacher- Background
- A teacher has a list of 50 student exam scores and needs to see how many students fall into each letter grade bracket.
- Problem
- Manually counting scores into ranges like 0-59, 60-69, etc., is prone to error.
- How to Use
- Paste the scores, select 'Custom Ranges', and input the grade boundaries (e.g., 'F:0-59', 'D:60-69').
- Example Config
-
rangeType: custom, customRanges: 'F:0-59\nD:60-69\nC:70-79\nB:80-89\nA:90-100' - Outcome
- A clear table showing the count and percentage of students in each grade category.
2. Price Tier Frequency Analysis
E-commerce Analyst- Background
- An analyst needs to understand the distribution of order values to optimize shipping thresholds.
- Problem
- The raw transaction data is too granular to identify common spending patterns.
- How to Use
- Input the transaction list, select 'Fixed Interval', and set the bin width to 50.
- Example Config
-
rangeType: fixed-interval, binWidth: 50, outputFormat: table - Outcome
- An HTML table displaying the frequency of orders within every $50 increment, highlighting the most common spending range.
Try with Samples
data-analysisEU VAT Number Samples
Collection of EU VAT numbers from all member states for validation testing
title token number
Number & Currency Samples
Text containing various number and currency formats for testing currency extraction
title token number
Passport Number Samples
Collection of valid passport number samples from various countries (China, USA, Japan, UK, Germany, etc.) for testing
title token number
Global Phone Number Samples
Collection of phone numbers from various countries for validation testing
title token number
Related Hubs
FAQ
What input formats are supported?
The tool accepts numbers separated by commas, spaces, or newlines, and can handle mixed separators automatically.
Can I define my own custom ranges?
Yes, select 'Custom Ranges' and enter your specific intervals in the format 'min-max' or 'label:min-max' on separate lines.
What is the difference between equal width and equal frequency?
Equal width divides the range into bins of the same size, while equal frequency attempts to put an equal number of data points into each bin.
Can I export the results?
Yes, you can output the analysis as JSON, CSV, an HTML table, or a summary report.
Is there a limit to the number of bins I can create?
You can configure between 2 and 100 bins for your distribution analysis.