Phitter review
A free, open-source toolkit for fitting, testing and visualizing probability distributions.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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.
Phitter pros and cons
- 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
Phitter fact sheet, pricing and score →
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