The chi-square test statistic calculator helps analyze categorical data by measuring discrepancy between observed and expected frequencies. It's used in hypothesis testing for goodness-of-fit, independence tests, and homogeneity assessments across various research fields including social sciences, biology, and market research.
1. Add observed and expected values using Add Row button
2. Ensure equal number of observations
3. Click Calculate to get chi-square statistic
4. Compare result with critical value from chi-square distribution table
5. Clear button resets all inputs
1. Designed HTML structure with input table
2. Added CSS styling for responsive layout
3. Implemented JavaScript functions for dynamic rows
4. Created chi-square calculation logic
5. Added validation and error handling
6. Integrated results display with interpretation
7. Included educational resources and FAQs
FAQs
What is a good chi-square test statistic?
A good chi-square statistic depends on degrees of freedom and significance level. Generally, lower values indicate better fit. Compare your result with critical values from chi-square distribution tables at 0.05 significance level for hypothesis testing.
Can I use this calculator for 2x2 contingency tables?
Yes, this calculator works for any contingency table format. Enter observed and expected values for each cell as separate rows. Ensure proper pairing of observed and expected values for accurate results.
How many decimal places should I use?
Use 2-3 decimal places for consistency. The calculator automatically rounds results to 3 decimal places for clarity while maintaining sufficient precision for statistical analysis.
What if observed and expected counts differ greatly?
Large discrepancies result in higher chi-square values, indicating potential significant differences. However, always consider sample size and degrees of freedom when interpreting results.
Is this calculator suitable for small sample sizes?
For small samples (n < 50), consider using Fisher's exact test instead. Chi-square test requires expected counts ≥5 in most cells for valid results.
How is degrees of freedom calculated?
Degrees of freedom = (rows - 1)(columns - 1). For goodness-of-fit tests: categories - 1. Our calculator automatically calculates DF based on input data size.
What does p-value mean in chi-square test?
The p-value indicates probability of observing the calculated chi-square statistic under the null hypothesis. Values ≤0.05 typically suggest rejecting the null hypothesis.
Can I use percentages instead of counts?
No, chi-square test requires actual frequency counts. Convert percentages back to original counts before inputting data for accurate calculations.
How to handle zero expected values?
Zero expected values make calculations undefined. Either collect more data or combine categories to ensure all expected values are ≥1, with most ≥5.
What's the difference between chi-square and t-test?
Chi-square tests categorical data relationships, while t-tests compare means of continuous data between groups. Use chi-square for frequency comparisons and t-tests for measurement comparisons.
