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Answer:
We are confident at 95% that the true proportion of people who made their visit because of a coupon they'd receive in the mail is between (0.236;0.304).
Step-by-step explanation:
A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval". Â
The margin of error is the range of values below and above the sample statistic in a confidence interval. Â
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean". Â
Description in words of the parameter p Â
[tex]p[/tex] represent the real population proportion of people who made their visit because of a coupon they'd receive in the mail.
[tex]\hat p[/tex] represent the estimated proportion of people who made their visit because of a coupon they'd receive in the mail.
n=640 is the sample size required Â
[tex]z_{\alpha/2}[/tex] represent the critical value for the margin of error Â
The population proportion have the following distribution Â
[tex]p \sim N(p,\sqrt{\frac{p(1-p)}{n}})[/tex] Â
Numerical estimate for p Â
In order to estimate a proportion we use this formula: Â
[tex]\hat p =\frac{X}{n}[/tex] where X represent the number of people with a characteristic and n the total sample size selected. Â
[tex]\hat p=\frac{173}{640}=0.270[/tex] represent the estimated proportion of people who made their visit because of a coupon they'd receive in the mail.
Confidence interval Â
The confidence interval for a proportion is given by this formula Â
[tex]\hat p \pm z_{\alpha/2} \sqrt{\frac{\hat p(1-\hat p)}{n}}[/tex] Â
For the 95% confidence interval the value of [tex]\alpha=1-0.95=0.05[/tex] and [tex]\alpha/2=0.025[/tex], with that value we can find the quantile required for the interval in the normal standard distribution. Â
[tex]z_{\alpha/2}=1.96[/tex] Â
And replacing into the confidence interval formula we got: Â
[tex]0.270 - 1.96 \sqrt{\frac{0.270(1-0.270)}{640}}=0.236[/tex] Â
[tex]0.270 + 1.96 \sqrt{\frac{0.270(1-0.270)}{640}}=0.304[/tex] Â
And the 95% confidence interval would be given (0.236;0.304). Â
We are confident at 95% that the true proportion of people who made their visit because of a coupon they'd receive in the mail is between (0.236;0.304).