Chi-Square Calculator

This calculator runs a one-sample chi-square goodness-of-fit test, checking whether the counts you have observed across a set of categories differ from what you would expect by chance, or whether the pattern points to something more than random variation. Start by entering the number of categories you are comparing, then type in the observed frequency for each one as it appears in your data. The calculator works out the expected frequency for every category, splitting the total observed count evenly across categories, along with the difference between observed and expected and each category's contribution to the chi-square statistic. These figures are summed to give you the overall chi-square value, the degrees of freedom, and the critical value needed to reject the null hypothesis at the standard 0.05 significance level. Where you enter exactly two categories, Yates' continuity correction is applied automatically to reduce bias in the calculation. The final result tells you plainly whether your chi-square value clears the critical threshold, meaning you can safely reject the null hypothesis that the categories occur with equal frequency, or whether it falls short, meaning the observed differences could plausibly be down to chance. This is a useful check for survey responses, dice or coin trials, market research counts and any dataset where you are testing category frequencies against an expected even split.

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