p value calculator from chi square

Chi-Square p-Value Calculator

Use this tool to calculate the right-tail p-value from a chi-square statistic and degrees of freedom.

Note: For chi-square tests, the p-value is typically the upper-tail probability: P(X ≥ χ²).

What this calculator does

A chi-square test gives you a test statistic (χ²). To decide whether your result is statistically significant, you need the p-value. This calculator converts your chi-square statistic and degrees of freedom into a p-value instantly.

It is useful for common procedures like:

  • Chi-square goodness-of-fit test
  • Chi-square test of independence (contingency tables)
  • Chi-square test of homogeneity

How to calculate p-value from chi-square

The p-value for a chi-square test is the area in the right tail of the chi-square distribution beyond your observed statistic. In notation:

p-value = P(Χ²df ≥ χ²observed)

Where:

  • χ²observed is your computed test statistic
  • df is the degrees of freedom
  • Χ²df is a chi-square random variable with df degrees of freedom

Under the hood, this uses the regularized incomplete gamma function, which is the standard numerical method used in statistical software.

Step-by-step example

Example values

  • Chi-square statistic: χ² = 10.83
  • Degrees of freedom: df = 4
  • Significance level: α = 0.05

Enter these values in the calculator. You’ll get a p-value around 0.0285. Because 0.0285 is less than 0.05, you reject the null hypothesis at the 5% significance level.

Interpreting the result

General interpretation guide

  • p < α: statistically significant; reject H₀.
  • p ≥ α: not statistically significant; fail to reject H₀.

A small p-value means your observed data would be unlikely if the null hypothesis were true. It does not measure effect size or practical importance.

Common degrees of freedom formulas

Goodness-of-fit test

df = k - 1 - m, where k is number of categories and m is number of estimated parameters.

Test of independence / homogeneity

df = (r - 1)(c - 1), where r is rows and c is columns in your contingency table.

Mistakes to avoid

  • Using the wrong degrees of freedom formula.
  • Treating p-value as proof that the alternative hypothesis is true.
  • Ignoring assumptions, such as expected counts being sufficiently large.
  • Reporting significance without context, confidence intervals, or effect size.

Quick FAQ

Is this a one-tailed or two-tailed p-value?

For chi-square tests, it is normally a right-tailed probability. So this calculator returns the right-tail p-value.

Can degrees of freedom be non-integer?

In most introductory chi-square tests, df is an integer. Numerically, the distribution is defined for any positive df, and this calculator supports positive values.

What if p-value is extremely small?

Extremely small p-values may display in scientific notation (for example, 2.1e-8), which still indicates strong evidence against the null hypothesis.

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