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 reject the null hypothesis, and we can say the the proportion of men with red/green color blindness.is significanlty higher than the proportion of women with red/green color blindness.
Step-by-step explanation:
Data given and notation
represent the number of men with red/green color blindness.
represent the number of women with red/green color blindness.
sample of male slected
sample of female selected
represent the proportion of male with red/green color blindness.
represent the proportion of female with red/green color blindness.
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 proportion of men with red/green color blindness. is higher than the proportionof women with red/green color blindness. , 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 reject the null hypothesis, and we can say the the proportion of men with red/green color blindness.is significanlty higher than the proportion of women with red/green color blindness.
