Chi-Square Test Calculator
Calculate chi-square statistic for goodness of fit and independence testing
About this calculator
The Chi-Square Test Calculator is a statistical tool that helps researchers and students perform chi-square tests for goodness of fit and independence testing. This calculator determines whether observed data significantly differs from expected values or whether two categorical variables are independent. It's essential for hypothesis testing in research, quality control, and data analysis across fields like psychology, biology, and business analytics.
How to use
Enter your observed frequencies and expected frequencies (or let the calculator compute expected values for independence tests). Select your test type: goodness of fit or test of independence. The calculator will compute the chi-square statistic, degrees of freedom, and p-value to help you determine statistical significance.
Frequently asked questions
What's the difference between goodness of fit and independence tests?
Goodness of fit tests whether data matches an expected distribution, while independence tests examine if two categorical variables are related.
How do I interpret the p-value result?
If p-value is less than your significance level (usually 0.05), reject the null hypothesis and conclude statistical significance.
What are the assumptions for chi-square tests?
Data must be categorical, observations independent, and expected frequencies should be at least 5 in each cell.