We have to perform an hypothesis test on the proportion.
In this case we should use a z-test.
The claim is that the proportion of millonaires that can wiggle their ears is different from 16%.
Then, the null and alternative hypothesis are:
[tex]\begin{gathered} H_0:\pi=0.16 \\ H_a:\pi\ne0.16 \end{gathered}[/tex]
The significance level is 0.01.
The sample has a size n = 342.
The sample proportion is p = 58/342 = 0.17.
The standard error of the proportion is:
[tex]\sigma_p=\sqrt{\frac{\pi(1-\pi)}{n}}=\sqrt{\frac{0.16\cdot0.84}{342}}\approx\sqrt{0.000393}\approx0.0198[/tex]
Then, we can calculate the z-statistic as:
[tex]z=\frac{p-\pi-0.5\/n}{\sigma_p}=\frac{0.17-0.16-0.5\/342}{0.0198}\approx\frac{0.0085383}{0.0198}\approx0.431[/tex]
This test is a two-tailed test, so the P-value for this test is calculated as:
[tex]2\cdot P(z>0.431)\approx2\cdot0.333\approx0.666[/tex]
As the P-value (0.666) is greater than the significance level (0.01), the effect is not significant.
The null hypothesis failed to be rejected.
At a significance level of 0.01, there is not enough evidence to support the claim that the proportion of millonaires that can wiggle their ears is different from 16%.
Answer:
a) For this study we should use a z-test.
b) H0: p = 0.16
Ha: p ≠ 0.16
c) z = 0.431
d) p-value = 0.666
e) The p-value is greater than α.
f) Based on this we should not reject the null hypothesis.
g) The data suggest the population proportion is not significantly different from 16% at α = 0.01, so there is statistically insignificant evidence to conclude that the population proportion of millonaires who can wiggle their ears is different from 16%.