Respuesta :
Using the z-distribution, it is found that the p-value is of 0.03.
At the null hypothesis, it is tested if the proportion is of 0.5, that is:
[tex]H_0: p = 0.5[/tex]
At the alternative hypothesis, it is tested if the proportion is different of 0.5, that is:
[tex]H_a: p \neq 0.5[/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 = 0.5, n = 150, \overline{p} = \frac{62}{150} = 0.4133[/tex]
Hence, the value of the test statistic is:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
[tex]z = \frac{0.4133 - 0.5}{\sqrt{\frac{0.5(0.5)}{150}}}[/tex]
[tex]z = -2.12[/tex]
The p-value is found using a z-distribution calculator, with z = -2.12 and a two-tailed test, as we are testing if the mean is different of a value, hence it is of 0.03.
To learn more about the use of the z-distribution for hypothesis tests, you can take a look at https://brainly.com/question/16313918
