Chi-Square to P-Value Calculator
Convert chi-square test statistics to p-values and assess statistical significance.
Calculate P-Value from Chi-Square
Table of Contents
What is Chi-Square Test?
The chi-square test is a statistical test used to determine if there is a significant association between categorical variables. It compares observed frequencies with expected frequencies under the null hypothesis.
- Tests for categorical data
- Compares observed vs expected frequencies
- Uses chi-square distribution
- Requires degrees of freedom
P-Value Interpretation
p < 0.05
Statistically significant
p < 0.01
Highly significant
p < 0.001
Very highly significant
p ≥ 0.05
Not statistically significant
Degrees of Freedom
Contingency Table (r-1)(c-1)
For a contingency table with r rows and c columns, degrees of freedom = (r-1)(c-1)
Goodness of Fit k-1
For a goodness of fit test with k categories, degrees of freedom = k-1
Independence Test (r-1)(c-1)
For testing independence between two categorical variables, degrees of freedom = (r-1)(c-1)
Common Examples
Example 1 Chi-Square = 3.84, df = 1
p-value ≈ 0.05 (borderline significant)
Example 2 Chi-Square = 6.63, df = 1
p-value ≈ 0.01 (highly significant)
Example 3 Chi-Square = 10.83, df = 1
p-value ≈ 0.001 (very highly significant)