Chi-Square Goodness of Fit Calculator
Enter the observed counts and the expected counts or proportions, in the same order.
Your numbers
Your results
Chi-Square Goodness of Fit Calculator by TheCalcTools
How the Chi-Square Goodness of Fit Calculator works
Pearson’s statistic adds up (observed − expected)² ÷ expected over all categories. Expected values entered as proportions are scaled to the observed total.
Compare it with the chi-square distribution with (categories − 1) degrees of freedom. The test needs expected counts of about 5 or more in each category.
The formula
Worked example
Using the default values shown in the calculator:
| Observed counts | 48, 35, 15, 2 |
|---|---|
| Expected counts or proportions (scaled automatically) | 0.45, 0.35, 0.15, 0.05 |
| Significance level α | 0.05 |
- χ² = 2.0000 with 3 degrees of freedom, p = 0.572407.
- No significant difference from the expected distribution.
Result:
| Chi-square statistic | 2.0000 |
|---|---|
| Degrees of freedom | 3 |
| p-value | 0.572407 |
| Conclusion | No significant difference from the expected distribution |
| Expected count check | All expected counts are at least 5 |
Frequently asked questions
What does a large chi-square mean?
The observed counts are far from what you expected. The p-value tells you how surprising that is if the expected distribution were true.
Sources and further reading
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This calculator gives estimates for information only. Check important results independently before you rely on them. See our disclaimer.
