About Scientific Histogram Generator & Frequency Analyzer
Publication-ready frequency distribution builder for empirical datasets. Features automated statistical bin width calculation using Sturges’ rule, Scott’s normal reference rule, and the Freedman-Diaconis rule. Includes a fitted normal bell curve overlay and interactive SVG export.
Key Capabilities & Features
- Three scientific binning rules: Sturges (default), Scott’s normal rule, and Freedman-Diaconis (IQR-based)
- Fitted Gaussian bell curve overlay showing theoretical normal distribution over observed bars
- Detailed frequency table reporting class intervals [x₀, x₁), absolute frequencies, relative percentages, and densities
- Publication-ready SVG export with clean axes, bin tick marks, and count callouts
- Zero external charting libraries: rendered with pure responsive browser vector graphics
How to Use Scientific Histogram Generator & Frequency Analyzer
Paste Numerical Data
Enter observations separated by commas, spaces, or line breaks.
Select Binning Algorithm
Choose Sturges, Scott, or Freedman-Diaconis for optimal class intervals.
Toggle Normal Curve Overlay
Check the Gaussian overlay box to visually assess data normality.
Review Frequency Table
Inspect exact counts and densities for every bin in your distribution.
Privacy & In-Browser Execution Guarantee
100% Client-Side. Histogram binning and SVG vector rendering run entirely on your device.
Frequently Asked Questions
When is Freedman-Diaconis binning preferable to Sturges?
Freedman-Diaconis is superior for non-normal or heavy-tailed distributions because it relies on the Interquartile Range (IQR) rather than the sample standard deviation, making it resilient to outliers.
What does density mean on a histogram?
Density equals relative frequency divided by bin width, ensuring the total area of the histogram bars sums to 1.0, directly comparable to continuous probability density functions.