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Exercises 3.112 to 3.115 give information about the proportion of a sample that agree with a certain statement. Use StatKey or other technology to find a confidence interval at the given confidence level for the proportion of the population to agree, using percentiles from a bootstrap distribution. StatKey tip: Use "CI for Single Proportion" and then "Edit Data" to enter the sample information. Find a \(95 \%\) confidence interval if 180 agree in a random sample of 250 people.

Short Answer

Expert verified
After following all these steps, you should be able to find the 95% confidence interval for the proportion of the population that agrees with the statement. This is your short answer, represented as an interval (lower bound, upper bound).

Step by step solution

01

Define The Sample Proportion

To determine the confidence interval, we first need to identify the sample proportion. This is computed by dividing the number of people who agreed (i.e., 180) by the total number of people in the sample (i.e., 250). This can be represented as \(p =\frac{180}{250}\). Calculate this value.
02

Find Standard Error

The next step is to find the standard error (SE) for the proportion. The SE for the proportion can be calculated by the formula \[\sqrt{ \frac{p(1 - p)}{n} }\] where \(p\) is the sample proportion calculated from step 1 and \(n\) is the number of people in the sample. Compute this value.
03

Determine Confidence Interval

The confidence interval can be found by taking the sample proportion and adding/subtracting the margin of error to it. The margin of error (E) is calculated by multiplying the standard error (SE) by the z-score for the desired confidence level. For a 95% confidence level, the z-score is 1.96. Hence, the confidence interval is \[p \pm E = p \pm 1.96 * SE\]. Calculate upper and lower bounds of the interval.

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