Respuesta :
Answer:
a) The null and alternative hypothesis are:
[tex]H_0: \pi=0.3\\\\H_a:\pi\neq 0.3[/tex]
b) The point estimate for the true proportion is the sample proportion, and has a value of p=0.48.
[tex]p=X/n=24/50=0.48[/tex]
c) The conclusion is that there is enough evidence to support the claim that the proportion of stocks that went up the same day differs from 30%.
Step-by-step explanation:
This is a hypothesis test for a proportion.
The claim is that the proportion of stocks that went up the same day differs from 30%.
Then, the null and alternative hypothesis are:
[tex]H_0: \pi=0.3\\\\H_a:\pi\neq 0.3[/tex]
The significance level is 0.01.
The sample has a size n=50.
The point estimate for the true proportion is the sample proportion, and has a value of p=0.48.
[tex]p=X/n=24/50=0.48[/tex]
The standard error of the proportion is:
[tex]\sigma_p=\sqrt{\dfrac{\pi(1-\pi)}{n}}=\sqrt{\dfrac{0.3*0.7}{50}}\\\\\\ \sigma_p=\sqrt{0.004}=0.065[/tex]
Then, we can calculate the z-statistic as:
[tex]z=\dfrac{p-\pi+0.5/n}{\sigma_p}=\dfrac{0.48-0.3-0.5/50}{0.065}=\dfrac{0.17}{0.065}=2.623[/tex]
This test is a two-tailed test, so the P-value for this test is calculated as:
[tex]P-value=2\cdot P(z>2.623)=0.009[/tex]
As the P-value (0.009) is smaller than the significance level (0.01), the effect is significant.
The null hypothesis is rejected.
There is enough evidence to support the claim that the proportion of stocks that went up the same day differs from 30%.