Chi-Square Test Calculator
Calculate chi-square test statistic and p-value for goodness of fit and independence tests
About this calculator
The Chi-Square Test Calculator performs statistical analysis to determine if observed data differs significantly from expected values. It calculates the chi-square test statistic and p-value for both goodness of fit tests (comparing observed vs. expected frequencies) and independence tests (examining relationships between categorical variables). This tool is essential for researchers, students, and analysts conducting hypothesis testing in fields like psychology, biology, market research, and quality control to make data-driven decisions with statistical confidence.
How to use
Input your observed frequencies and expected frequencies (or theoretical proportions) into the calculator fields. Select whether you're performing a goodness of fit test or independence test. Click calculate to get the chi-square statistic, degrees of freedom, and p-value, then compare the p-value to your significance level to determine statistical significance.
Frequently asked questions
What is a good p-value for chi-square tests?
A p-value less than 0.05 typically indicates statistical significance, meaning you can reject the null hypothesis with 95% confidence.
What's the difference between goodness of fit and independence tests?
Goodness of fit tests compare observed data to expected distributions, while independence tests examine relationships between two categorical variables.
What are the assumptions for chi-square tests?
Data must be categorical, observations independent, and expected frequencies should be at least 5 in each category for reliable results.