Answer :
Using the z-distribution, it is found that the value of the test statistic is z = 10.33.
At the null hypothesis, it is tested if the proportion is of [tex]\frac{3}{4} = 0.75[/tex], hence:
[tex]H_0: p = 0.75[/tex]
At the alternative hypothesis, it is tested if the proportion is different, that is:
[tex]H_1: p \neq 0.75[/tex]
The test statistic is given by:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
In which:
- [tex]\overline{p}[/tex] is the sample proportion.
- p is the proportion tested at the null hypothesis.
- n is the sample size.
For this problem, the parameters are: [tex]p = 0.75, \overline{p} = 0.89, n = 1201[/tex]
Hence:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
[tex]z = \frac{0.89 - 0.75}{\sqrt{\frac{0.75(0.25)}{1021}}}[/tex]
[tex]z = 10.33[/tex]
A similar problem is given at https://brainly.com/question/24330815