Phitter
Phitter: A free, open-source toolkit for fitting, testing and visualizing probability distributions. Ranked #67 of 106 in Statistical Analysis Software by our editors (3.0/10); pricing: Free plan; best for analysts comparing probability distributions.
At a glance
- Editor score3.0 / 10
- PricingFree plan
- Best forAnalysts comparing probability distributions
- Free planYes
- Paid fromFree
- DeploymentBoth
- Facts checked23 Sep 2026
Where it wins
- Fits continuous and discrete distributions with parameter estimation
- Ranks candidates using goodness-of-fit results and information criteria
- Offers browser and Python workflows with local browser calculation
Where it doesn't
- Focused on probability distributions rather than regression or Bayesian analysis
- Support is provided through documentation
- Imports are limited to TXT, CSV, XLSX and public URLs
Our verdict on Phitter
Phitter is open-source statistical software for analysts who need to fit probability distributions to observed data. It handles both continuous and discrete distributions, estimates parameters, compares candidate models, runs goodness-of-fit tests, and presents the results visually. The browser application suits interactive analysis, while the Python package supports notebooks, scripts, and reproducible pipelines for solo, small, and mid-market teams.
Distribution fitting is the product’s central strength. Phitter ranks candidates using goodness-of-fit results and information criteria, then provides Kolmogorov–Smirnov, Anderson–Darling, and chi-square tests. Its visual output includes histograms, density or mass views, cumulative-distribution plots, and Q–Q plots, giving analysts several ways to inspect how a fitted model represents their observations. Data can be pasted into the browser or imported from TXT, CSV, XLSX, and public URLs.
The platform covers web, API, and self-hosted deployment, and browser calculations run locally through Pyodide/WebAssembly. That combination gives users a choice between an accessible web workflow and Python-based automation. Phitter’s scope is deliberately narrower than a general statistical suite: its published capabilities center on distribution fitting and related diagnostics rather than regression or Bayesian analysis. Teams needing those model families should choose a broader statistics environment, while analysts focused on probability-distribution selection and testing get a specialized free tool with a clear workflow.
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Phitter pricing
Phitter fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment | Both |
| Statistical tests | Yes |
| Regression models | No |
| Scripting support | Yes |
| Bayesian analysis | No |
| Data import formats | TXT, CSV, XLSX, public URL |
| Deployment | Cloud, Self-hosted |
| Platforms | Web |
| Support | Docs |
| Built for | Solo, Small business, Mid-market (editorial estimate) |
| Pricing | Free plan |
| Website | phitter.io |
| Facts checked | 23 Sep 2026 |
Alternatives to Phitter
- RA free, programmable environment for statistical analysis, modeling, visualization, and data import.9.4
- StataA broad, scriptable desktop environment for professional and reproducible applied analysis.9.3
- IBM SPSS StatisticsA broad desktop statistics suite with testing, modeling, forecasting, reporting, and R/Python integration.9.2
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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