Answer:
a
The 95% confidence interval is [tex]0.0503 < p < 0.1297[/tex]
b
The sample proportion is [tex]\r p = 0.09[/tex]
c
The critical value is [tex]Z_{\frac{\alpha }{2} } = 1.96[/tex]
d
The standard error is [tex]SE =0.020[/tex]
Step-by-step explanation:
From the question we are told that
The sample size is n = 200
The number of defective is k = 18
The null hypothesis is [tex]H_o : p = 0.08[/tex]
The alternative hypothesis is [tex]H_a : p > 0.08[/tex]
Generally the sample proportion is mathematically evaluated as
[tex]\r p = \frac{18}{200}[/tex]
[tex]\r p = 0.09[/tex]
Given that the confidence level is 95% then the level of significance is mathematically evaluated as
[tex]\alpha = 100 - 95[/tex]
[tex]\alpha = 5\%[/tex]
[tex]\alpha = 0.05[/tex]
Next we obtain the critical value of [tex]\frac{ \alpha }{2}[/tex] from the normal distribution table, the value is
[tex]Z_{\frac{\alpha }{2} } = 1.96[/tex]
Generally the standard of error is mathematically represented as
[tex]SE = \sqrt{\frac{\r p (1 - \r p)}{n} }[/tex]
substituting values
[tex]SE = \sqrt{\frac{0.09 (1 - 0.09)}{200} }[/tex]
[tex]SE =0.020[/tex]
The margin of error is
[tex]E = Z_{\frac{ \alpha }{2} } * SE[/tex]
=> [tex]E = 1.96 * 0.020[/tex]
=> [tex]E = 0.0397[/tex]
The 95% confidence interval is mathematically represented as
[tex]\r p - E < \mu < p < \r p + E[/tex]
=> [tex]0.09 - 0.0397 < \mu < p < 0.09 + 0.0397[/tex]
=> [tex]0.0503 < p < 0.1297[/tex]
