g>Use your df to look up the critical value of the chi-square test, also called the chi-square-crit. So for a test with 1 df (degree of freedom), the "critical" value of the
chi-square statistic is 3.84.
What does critical value mean?
Basically, if the chi-square you calculated was bigger than the critical value in the table,
then the data did not fit the model, which means you have to reject the null hypothesis.
On the other hand, if the chi-square you calculated was smaller than the critical value, then the
data did fit the model, you fail to reject the null hypothesis, and go out and party.*
(*Assuming you don’t want to reject the null. Which you usually
don’t.)
Why do you think the chi-square-crit increases as the degrees of freedom increases?
Fine print: some tables have many columns, one for each p-value you might be interested in.
In that case, you first need to find the 0.05 p-value (or any other p-value you’re asked for), then the
df, then the chi-square-crit.
Even finer print: or, you may be asked to find the p-value corresponding to the chi-square-calc.
In that case you have to find the right df first, then find the two chi-square-crits that your chi-square-calc
falls between, then note the p-value.