Hypothesis Test Calculator
Overview
The Hypothesis Test Calculator performs common statistical tests including t-tests, chi-square tests, and ANOVA with automatic p-value calculation and interpretation. Select your test type, input your data, and receive test statistics, p-values, and plain-language conclusions about statistical significance at your chosen alpha level.
Tips
- Use paired t-tests for before/after measurements on the same subjects, not independent two-sample t-tests
- For comparing more than two groups, use ANOVA instead of multiple t-tests to avoid inflating Type I error
- A p-value close to your alpha threshold (e.g., p=0.048 with alpha=0.05) suggests borderline significance - consider collecting more data
- Small p-values indicate statistical significance but don’t measure effect size - a tiny difference can be significant with large samples
- Check your assumptions: t-tests assume approximate normality, ANOVA assumes equal variances across groups
- The chi-square test requires expected frequencies of at least 5 in each cell for valid results
- Statistical significance (p < alpha) doesn’t always mean practical significance - always consider the magnitude of the effect