TATITIC CALCULATOR
Chi Square
A precise tool.
What is the Chi Square & How does it work?
The chiβsquare test assesses how well observed categorical data fit an expected distribution.
It is widely used for goodnessβofβfit, test of independence, and homogeneity across contingency tables.
The test statistic aggregates the squared differences between observed (O) and expected (E) counts, scaled by the expected counts.
\chi^2 = \sum \frac{(O_i – E_i)^2}{E_i}
O_i = observed frequency, E_i = expected frequency
Parameters
Result
β
Frequently Asked Questions
What is a chi-square test?
A chi-square test is a statistical method used to determine if there is a significant difference between the expected frequencies and the observed frequencies in one or more categories.
When should I use the Chi Square Calculator?
Use this calculator when you need to perform a goodness-of-fit test, a test of independence, or a homogeneity test across contingency tables.
How do I interpret the chi-square value?
The higher the chi-square value, the greater the difference between observed and expected frequencies. Compare your calculated chi-square value to a critical value from the chi-square distribution table to determine statistical significance.
What is the formula for calculating chi-square?
The chi-square formula is chi^2 = sum frac{(O_i – E_i)^2}{E_i}, where O_i is the observed frequency and E_i is the expected frequency for each category.
Can I use this calculator for continuous data?
No, the Chi Square Calculator is designed for categorical data. For continuous data, consider using other statistical tests like t-tests or ANOVA.
What does a p-value tell me in a chi-square test?
The p-value indicates the probability of observing your data (or more extreme) if the null hypothesis is true. A small p-value (typically β€ 0.05) suggests rejecting the null hypothesis.
How do I determine degrees of freedom for a chi-square test?
Degrees of freedom are calculated based on the number of categories minus one for a goodness-of-fit test, or (rows – 1) * (columns – 1) for a test of independence.
Results are for informational purposes only and do not constitute professional advice.