Respuesta :
Answer:
b. Keep the sample size the same and decrease the confidence level.
Step-by-step explanation:
We first have to find the critical value of z, which depends of the confidence level.
90% confidence level
We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:
[tex]\alpha = \frac{1-0.9}{2} = 0.05[/tex]
Now, we have to find z in the Ztable as such z has a pvalue of [tex]1-\alpha[/tex].
So it is z with a pvalue of [tex]1-0.05 = 0.95[/tex], so [tex]z = 1.645[/tex]
99% confidence level
We have that to find our [tex]\alpha[/tex] level, that is the subtraction of 1 by the confidence interval divided by 2. So:
[tex]\alpha = \frac{1-0.99}{2} = 0.005[/tex]
Now, we have to find z in the Ztable as such z has a pvalue of [tex]1-\alpha[/tex].
So it is z with a pvalue of [tex]1-0.005 = 0.995[/tex], so [tex]z = 2.575[/tex]
The width of the interval is:
[tex]W = z*\frac{\sigma}{\sqrt{n}}[/tex]
In which [tex]\sigma[/tex] is the standard deviation of the population and n is the size of the sample.
So, as z increses, so does the width. If z decreases, the width decreases. Lower confidence levels have lower values of z.
As n increases, the width decreses.
What will result in a reduced interval width?
b. Keep the sample size the same and decrease the confidence level.
