Answer:
If we compare the p value and using any significance level for example 
always 
so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the the two proportions are not statistically different at 5% of significance
Step-by-step explanation:
Data given and notation
represent the number of correct answers for university degree holders
represent the number of correct answers for university non-degree holders
sample 1 selected
sample 2 selected
represent the proportion of correct answers for university degree holders
represent the proportion of correct answers for university non-degree holders
z would represent the statistic (variable of interest)
represent the value for the test (variable of interest)
Concepts and formulas to use
We need to conduct a hypothesis in order to check if the proportions are different between the two groups, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
We need to apply a z test to compare proportions, and the statistic is given by:
(1)
Where 
Calculate the statistic
Replacing in formula (1) the values obtained we got this:
Statistical decision
For this case we don't have a significance level provided 
, but we can calculate the p value for this test.
Since is a one side test the p value would be:
If we compare the p value and using any significance level for example always so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the the two proportions are not statistically different at 5% of significance
