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Sagot :
Answer:
The value of teh test statistic is [tex]z = 5.54[/tex]
The p-value of the test is 0 < 0.05, which means that there is significant evidence to conclude that the proportion differs from 0.2.
Step-by-step explanation:
The test statistic is:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
In which X is the sample mean, [tex]\mu[/tex] is the value tested at the null hypothesis, [tex]\sigma[/tex] is the standard deviation and n is the size of the sample.
0.2 is tested at the null hypothesis:
This means that [tex]\mu = 0.2, \sigma = \sqrt{0.2*0.8} = 0.4[/tex]
Using the sample results p^=0.27 with n=1003
This means that [tex]X = 0.27, n = 1003[/tex]
Value of the test statistic:
[tex]z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \frac{0.27 - 0.2}{\frac{0.4}{\sqrt{1003}}}[/tex]
[tex]z = 5.54[/tex]
P-value of the test and decision:
The p-value of the test is the probability that the sample proportion differs from 0.2 by at least 0.07, which is P(|z| > 5.54), that is, 2 multiplied by the p-value of z = -5.54.
Looking at the z-table, z = -5.54 has a p-value of 0.
2*0 = 0.
The p-value of the test is 0 < 0.05, which means that there is significant evidence to conclude that the proportion differs from 0.2.
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