An Outliers Effect. A good way to judge the effect of an outlier is to do your analysis twice, once with the outlier and a second time without it. The data in Exercise 20.32 follow a Normal distribution quite closely except for one patient with HAV angle 50 degrees, a high outlier. Find the 95% confidence interval for the population mean based

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An Outliers Effect. A good way to judge the effect of an outlier is to do your analysis twice, once with the outlier and a second time without it. The data in Exercise 20.32 follow a Normal distribution quite closely except for one patient with HAV angle 50 degrees, a high outlier.   Find the 95% confidence interval for the population mean based on the 37 patients who remain after you drop the outlier.  Compare your interval in part (a) with your interval from Exercise 20.32. What is the most important effect of removing the outlier?

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