Chi-Square to P-Value - Basic Stats In a review problem for a class, we were asked to perform a Chi-Square Test Statistic for a 2x2 Table without a continuity correction. In the answer key, my professor included the following:

I totally follow all of the math up until the p-value portion. Where did she get the 0.25 p-value? Any suggestions you have would be much appreciated! Thank you!

I am currently thinking about it such that: if the x2observed < 0.25 alpha's X2crit (which is 1.32) then it definitely will be less than 0.05 alpha's x2 crit of 3.84? However, where the p-values come into play is still unclear to me.

Here $0.25$ is not a p-value, but the significance level, $\alpha$, to which the p-value is compared. The significance level is decided upon before the experiment and any calculations The results are then considered significant only if $p < \alpha$.
The value of $P(\chi_{df=1}^2\geq 0.607)$ is either taken from a table (e.g., like this one) or computed using a typical statistical software.
Remark:  In fact $0.25$ is a very high number for a significance level, so most likely it is just the approximate value of $P(\chi_{df=1}^2\geq 0.607)$.
