Answer:
a) Null hypothesis:
Alternative hypothesis:
b) represent the proportion of men that replied yes
represent the proportion of women that replied yes
c)
So the p value is a very low value and using the significance level given always so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion of men is significant higher than the proportion of female .
Explanation:
1) Data given and notation
represent the number of men that replied yes
represent the number of women that replied yes
sample of male selected
sample of demale selected
represent the proportion of men that replied yes
represent the proportion of women that replied yes
z would represent the statistic (variable of interest)
represent the value for the test (variable of interest)
2) Concepts and formulas to use
We need to conduct a hypothesis in order to check if the proportion for men that replied yes is higher than the proportion of women that replied yes:
Null hypothesis:
Alternative hypothesis:
We need to apply a z test to compare proportions, and the statistic is given by:
(1)
Where
3) Calculate the statistic
Replacing in formula (1) the values obtained we got this:
4) 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 right tailed test the p value would be:
So the p value is a very low value and using the significance level given always so we can conclude that we have enough evidence to reject the null hypothesis, and we can say the the proportion of men is significant higher than the proportion of female .