AI Statistics App
Statisty combines online statistical calculators with AI-assisted explanations of statistical results. You can analyze your data in the browser and use AI help to better understand result tables, p-values, confidence intervals, effect sizes, assumptions, and statistical output.
What the AI Statistics App Does
The AI features in Statisty are designed to explain statistical results, not to replace the analysis itself. After calculating a test or model, AI assistance can help describe what a table contains, what individual values mean, and how the result can be read in the context of the selected analysis.
How AI Helps Interpret Statistics
- Explains result tables for statistical tests and models.
- Clarifies p-values, test statistics, confidence intervals, and effect sizes.
- Helps connect output to common reporting language.
- Supports users who need help understanding assumptions and statistical terminology.
Supported Statistical Analyses
Statisty includes calculators for common analyses such as t-tests, ANOVA, correlation, regression, chi-square tests, and non-parametric tests. AI explanations are most useful after the calculator has produced a concrete result table from your selected variables.
How to Use AI Statistical Interpretation
- Paste or enter your data into Statisty.
- Select the variables you want to analyze.
- Review the statistical output generated by the calculator.
- Use the AI help options on result tables when you need an explanation.
- Check the interpretation against your research question and study design.
If you want an online workflow for common tests without desktop software, Statisty can also be used as a free SPSS alternative.
Privacy and Data Handling
AI requests should be handled carefully because statistical output can contain sensitive information. Statisty keeps AI processing focused on the specific request and documents the workflow on the AI privacy page.
Limits of AI Statistical Interpretation
AI can help explain output, but it cannot decide whether your study design is valid, whether your data were collected correctly, or whether a result proves causation. Use AI explanations as support, and interpret statistical results together with assumptions, data quality, sample size, and subject-matter knowledge.