Chi-Square Test Calculator
Calculate chi-square statistic for goodness of fit and independence tests with critical values
About this calculator
The Chi-Square Test Calculator performs statistical analysis to determine if observed data significantly differs from expected values. It calculates the chi-square statistic for both goodness of fit tests (comparing observed frequencies to expected distributions) and independence tests (examining relationships between categorical variables). This tool provides critical values and p-values, helping researchers, students, and analysts make informed decisions about their hypotheses in fields like psychology, biology, market research, and quality control.
How to use
Enter your observed and expected frequencies into the calculator table. Select your significance level (typically 0.05) and degrees of freedom. Click calculate to get the chi-square statistic, critical value, and p-value. Compare results to determine if your data shows statistically significant differences or relationships.
Frequently asked questions
What is 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.
How do I determine degrees of freedom for my test?
For goodness of fit: df = categories - 1. For independence tests: df = (rows - 1) × (columns - 1).
What does a significant chi-square result mean?
A significant result (p < 0.05) suggests observed data differs meaningfully from expected values, rejecting the null hypothesis.