The p-value is a probability that measures the evidence against the null hypothesis. Lower probabilities provide stronger evidence against the null hypothesis.
Use the p-value to determine whether to reject or fail to reject the null hypothesis, which states that the variables are independent.
Minitab uses the chi-square statistic to determine the p-value.
Minitab does not display the p-value when any expected count is less than 1 because the results can be invalid.
To determine whether variables are independent, compare the p-value to the significance level. Usually, a significance level (denoted as α or alpha) of 0.05 works well. A significance level of 0.05 indicates a 5% risk of concluding that an association between the variables exists when there is no actual association.
- P-value ≤ α: The variables have a statistically significant association (Reject H0)
- If the p-value is less than or equal to the significance level, you reject the null hypothesis and conclude that there is a statistically significant association between the variables.
- P-value > α: Cannot conclude that the variables are associated (Fail to reject H0)
- If the p-value is larger than the significance level, you fail to reject the null hypothesis because there is not enough evidence to conclude that the variables are associated.
In these results, the p-value is 0.019. Because the p-value is less than α, you reject the null hypothesis. You can conclude that the variables are associated.
Chi-Square DF P-Value
Pearson 11.788 4 0.019
Likelihood Ratio 11.816 4 0.019