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Chi-Square Test of Independence
Formula
The chi-square test of independence determines whether there is a significant association between two categorical variables. It compares observed frequencies with the frequencies expected under independence.
If the chi-square statistic exceeds the critical value for the chosen significance level, the null hypothesis of independence is rejected.
Common use cases:
- Testing independence of categorical variables
- A/B testing significance
- Survey data analysis
Frequently Asked Questions
Dr. David Park
Applied Mathematician, PhD Mathematics
David holds a PhD in Applied Mathematics from MIT. He has published research on numerical methods and computational algorithms used in engineering and scientific calculators.
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