Using the z-distribution, since the p-value of the test is less than 0.01, there is enough evidence to conclude that the claim is correct.
At the null hypothesis, it is tested if there is not enough evidence that the proportion is above 0.5, hence:
[tex]H_0: p \leq 0.5[/tex]
At the alternative hypothesis, it is tested if there is enough evidence that the proportion is above 0.5, hence:
[tex]H_1: p > 0.5[/tex]
The test statistic is given by:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
In which:
For this problem, the parameters are:
[tex]n = 825, \overline{p} = \frac{500}{825} = 0.606, p = 0.5[/tex]
Hence the test statistic is:
[tex]z = \frac{\overline{p} - p}{\sqrt{\frac{p(1-p)}{n}}}[/tex]
[tex]z = \frac{0.606 - 0.5}{\sqrt{0.5(0.5)}{825}}}[/tex]
z = 6.1.
We have a right-tailed test, as we are testing if the proportion is greater than a value. Using a z-distribution calculator, with z = 6.1, the p-value is of 0.
Since the p-value is less than 0.01, there is enough evidence to conclude that the claim is correct.
More can be learned about the z-distribution at https://brainly.com/question/16313918
#SPJ1