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: Chapter 21: Confidence Intervals Example of a Confidence Interval for a population proportion, p: The public television sta
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(A) Using TI-84, press STAT, then TESTS, then 1-PropZTest

enter the data

x: 75

n: 300

c = 0.99

Click on CALCULATE

we get

(0.1856, 0.3144)

We are 99% confident that the true proportion of erros made by beginning programming students that are punctuation erros is between 0.1856 and 0.3144

(B) Using TI-84, press STAT, then TESTS, then 1-PropZTest

enter the data

x: 75

n: 300

c = 0.95

Click on CALCULATE

we get

(0.201,0.299)

this interval is shorted as compared to the 99% confidence interval

(C) z score for 99% confidence interval is 2.58, sample size is n = 300 and p = 75/300 = 0.25

Margin of error for 99% =

z*\sqrt{((1-\hat{p})*\hat{p})/n} \\ = 2.58*\sqrt{((1-0.25)*0.25)/300} \\ = 0.0645

z score for 95% confidence interval is 1.96, sample size is n = 300 and p = 75/300 = 0.25

Margin of error for 99% =

z*\sqrt{((1-\hat{p})*\hat{p})/n} \\ = 1.96 * \sqrt{((1-0.25)*0.25)/300} \\ = 0 .049

(D) Margin of error from part (B) = (Upper limit- lower limit)/2 = (0.299-0.201)/2 = 0.049

Yes, both the margin of errors are same. This is because both the methods providing us exactly same value using same input data

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