Why is it best to compare medians and interquartile ranges for these data, rather than comparing means and standard deviations? A. Some of these data have vastly different centers, and the median and interquartile range provide more reliable information in these circumstances. B. These data are fairly symmetric and do not have outliers, and the median and interquartile range provide more reliable information in these circumstances. C. Some of these data have outliers and/or are skewed, and the median and interquartile range are resistant to outliers. D. Some of these data have outliers and/or are skewed, and the median and interquartile range amplify the effects of outliers and skewness.

Outliers often characterize a lot of data. Outliers are extreme values which have obvious impact on the value of the standard deviation of a given distribution.

However, the median and interquartile range are resistant to outliers hence they can be used even in the presence of outliers in the distribution.

andromache andromache · Answer 2 · 2022-02-22T11:04:01+01:00

The best for comparing the medians and interquartile range is the first option

What are outliers?

Outliers refer to the attribute of a lot of data. It is considered to be an extreme value that should have an impact on the value of the standard deviation of a given distribution. But, the median and interquartile range should be resistant to outliers.

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