Free, accurate statistical calculators for everyone.
Statistical analysis should not require expensive software or a PhD. Stat-Tools was built to give students, researchers, healthcare workers, business analysts, and curious minds instant access to professional-grade statistical calculators — completely free, no sign-up required.
Our calculators are powered by Python's SciPy and NumPy together with exact in-browser math — the same methods trusted by scientists worldwide — so you get the same accuracy as SPSS, R, or Stata, free and instant. See our methodology & accuracy page for the details.
Mean, median, mode, standard deviation, variance, IQR, skewness, kurtosis, and more from raw data.
One-sample, two-sample independent, and paired t-tests with p-value and plain-English conclusions.
CI for a population mean (t-distribution) or proportion (z-distribution).
Required sample size for estimating a mean or proportion at a given confidence and margin of error.
PDF, CDF, z-scores, and tail probabilities for any normal distribution.
Pearson and Spearman correlation coefficients with p-value, 95% CI, and scatter plot.
Slope, intercept, R², residuals, and regression line chart.
Goodness of fit and independence tests with Cramér's V effect size.
F-statistic and p-value for comparing means across three or more groups.
Inferential tests (t-tests, ANOVA, regression, and more) are computed on a Python 3 backend using SciPy and NumPy — the standard scientific-computing libraries used by researchers worldwide — while our probability, combinatorics, and distribution tools use exact closed-form math directly in your browser. Both are cross-checked against SciPy's reference implementation.
Results should match those produced by R, SPSS, Excel (Analysis ToolPak), and other standard software. Read the full methodology & accuracy page, or report a discrepancy at [email protected].
Questions, bug reports, or feature requests? Email us at [email protected].
Stat-Tools is not a substitute for professional statistical consulting. Results should be interpreted by someone with appropriate statistical knowledge for critical research or business decisions.