In the article "On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals," by Schenker and Gentleman (American Statistician, Vol. 55, No. 3), the authors consider sample data in this statement: "Independent simple random samples, each of size 200, have been drawn, and 112 people in the first sample have the attribute, whereas 88 people in the second sample have the attribute." Based on the preceding results, what should you conclude about the equality of p1 and p2? Which of the three preceding methods is least effective in testing for the equality of p1 and p2?

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In the article &quot;On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals,&quot; by Schenker and Gentleman (American Statistician, Vol. 55, No. 3), the authors consider sample data in this statement: &quot;Independent simple random samples, each of size 200, have been drawn, and 112 people in the first sample have the attribute, whereas 88 people in the second sample have the attribute.&quot; Based on the preceding results, what should you conclude about the equality of p1 and p2? Which of the three preceding methods is least effective in testing for the equality of p1 and p2?

2abehn · Accepted Answer

p1 and p2 do not appear to be equal, because the hypothesis test from part (c) lead us to reject the claim that the proportions are equal. The least effective method is the method using the overlap of confidence intervals, becatise this was the only method that lead to a wrong conclusion. Equal, overlap of confidence intervals

In the article "On Judging the Significance of Differences by Examining the Overlap Between Confidence Intervals," by Schenker and Gentleman (American

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