I collect a random sample of size n from a population and compute a 95% confidence interval for the proportion I observe from the population. What could I do to produce a new confidence interval with a smaller width, smaller margin of error, based on these same data?

Respuesta :

Answer:

You should increase the size of your random sample, that is, increase the value of n.

Step-by-step explanation:

In a sample with a number n of people surveyed with a probability of a success of [tex]\pi[/tex], and a confidence interval [tex]1-\alpha[/tex], we have the following confidence interval of proportions.

[tex]\pi \pm z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

In which

z is the zscore that has a pvalue of [tex]1 - \frac{\alpha}{2}[/tex].

The margin of error is:

[tex]M = z\sqrt{\frac{\pi(1-\pi)}{n}}[/tex]

This means that as we increase the sample size(n), the margin of error decreases, as does the width of the confidence interval.

What could I do to produce a new confidence interval with a smaller width, smaller margin of error, based on these same data?

You should increase the size of your random sample, that is, increase the value of n.

RELAXING NOICE
Relax