Metric:
Ordinal:
Nominal:

Descriptive Statistics

Hypothesis test

Charts

Dependent variable:
Independent variables:

Regression
Free Statistics App
t-Test
One sample t-Test
Independent t-Test
Paired t-Test
Binomial Test
Chi-squared Test
ANOVA
One-way ANOVA
Two-way ANOVA
One-way ANOVA with repeated measures
Two-way ANOVA with repeated measures
Mann-Whitney U-test
Wilcoxon Test
Kruskal-Wallis Test
Friedman Test
Correlation
Pearson Correlation
Spearman's rank Correlation
Regression Analysis
Linear Regression
Logistic Regression
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Free SPSS Alternative
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About

Free SPSS Alternative

Statisty is a free online SPSS alternative for common statistical analyses. You can paste data into the browser, select variables, and calculate tests such as t-tests, ANOVA, correlation, regression, chi-square tests, and non-parametric tests without installing desktop software.

When Statisty Is a Good Alternative to SPSS

  • You need a fast browser-based tool for common statistical tests.
  • You want to analyze data without installing or licensing desktop software.
  • You work with typical student, thesis, teaching, research, or survey datasets.
  • You want clear result tables, charts, assumptions, p-values, and effect sizes.

What You Can Calculate Online

Statisty includes calculators for t-tests, ANOVA, correlation, regression, chi-square tests, and rank-based non-parametric tests such as the Mann-Whitney U test, Wilcoxon test, Kruskal-Wallis test, and Friedman test.

How Statisty Differs from SPSS

SPSS is a full desktop statistics package with a broad feature set for professional statistical workflows. Statisty focuses on a simpler online workflow for frequently used analyses: paste data, select variables, and review the automatically generated output. It is not a complete replacement for every SPSS feature, but it can be a useful free option for many everyday analyses.

AI Help for Statistical Interpretation

In addition to online calculators, Statisty includes AI-assisted statistical interpretation for explaining result tables, p-values, confidence intervals, assumptions, and effect sizes. The AI features are intended to help you understand the output, not to replace statistical judgment or research design decisions.

How to Start

  1. Paste your data into the table and keep variable names in the first row.
  2. Select the variables you want to analyze.
  3. Check the variable scale levels and selected test.
  4. Review descriptive statistics, charts, assumptions, and test results.
  5. Use the output to report your analysis or continue with AI-assisted explanation.

For a broader overview, see the online statistics software page.