Statistics

Chi-Square Calculator

Assess how well observed counts agree with expected counts using the chi-square goodness-of-fit test.

chi-squaregoodness of fitcategorical
Chi-square Goodness of Fit

Enter observed counts and expected counts to test distribution fit.

Chi-square statistic
1.1111
Degrees of freedom
2
p-value
0.573753

Chi-square statistic

χ² = Σ (Oᵢ − Eᵢ)² / Eᵢ

The calculator also reports the degrees of freedom (categories − 1) and the corresponding right-tail p-value.

How to use

  1. Enter observed counts and matching expected counts.
  2. Ensure expected counts are positive and align with observed categories.
  3. Review χ², degrees of freedom, and the p-value.

Example

Input: Observed = 50,45,40; Expected = 45,45,45

Output: χ² ≈ 2.778, df = 2, p ≈ 0.249

Student-friendly breakdown

This walkthrough emphasizes the most searched ideas for Chi-Square Calculator: chi square calculator, chi square p value calculator, chi square goodness of fit calculator, chi square test statistic calculator. Start with the formula above, then follow the guided steps to double-check your work. For quick revision, highlight the givens, plug into the equation, and finish by verifying your units.

Need more support? Use the links below to open the long-form guide, browse additional examples, or hop into adjacent calculators within the same topic — each one is a quick way to double-check your work or handle a related question without starting from scratch.

Deep dive & study plan

Chi-Square Calculator: Computes the chi-square statistic and p-value for goodness of fit. It's built around chi-square, goodness of fit, categorical, so you can go from a raw question to a checked answer without switching tools.

The math behind it: The calculator also reports the degrees of freedom (categories − 1) and the corresponding right-tail p-value. The core relationship is χ² = Σ (Oᵢ − Eᵢ)² / Eᵢ, shown above the calculator so you can see exactly how your inputs turn into the result.

To use it well: (1) Enter observed counts and matching expected counts. (2) Ensure expected counts are positive and align with observed categories. (3) Review χ², degrees of freedom, and the p-value. Keep your units consistent as you go, and re-run a case you already know the answer to — it's the fastest way to catch a typo before it throws off a result you're relying on.

Worked example: entering Observed = 50,45,40; Expected = 45,45,45 returns χ² ≈ 2.778, df = 2, p ≈ 0.249. Try swapping in your own numbers next, especially a case you're unsure about, before you use this for something that matters.

Quick retention checklist

  • Speak the formula aloud (or annotate it) so the relationships stick.
  • Write each step in your own words and compare with the numbered list above.
  • Swap in new numbers for the Example to make sure the calculator (and your logic) handles edge cases.
  • Check at least one related calculator below — it's the fastest way to confirm your numbers still line up from a different angle.

FAQ & notes

Can I test contingency tables?

This calculator handles goodness-of-fit tests. For contingency tables, flatten the observed counts and compute expected frequencies first.

What if expected counts are zero?

Chi-square requires all expected counts to be positive. Combine categories or use Fisher’s exact test if counts are too small.

What formula does the Chi-Square Calculator use?

The calculator also reports the degrees of freedom (categories − 1) and the corresponding right-tail p-value.

How do I use the Chi-Square Calculator?

Enter observed counts and matching expected counts. Ensure expected counts are positive and align with observed categories. Review χ², degrees of freedom, and the p-value.