Question at position 14 Any data value with a z-score less than –3 or greater than +3 is considered to be a(n) Question Blank 1 of 1[input].

Question

BlackTom AI · Accepted Answer

The question asks about the designation for a data value whose z-score falls far from the mean. Since a z-score represents the number of standard deviations a value is from the mean, extreme values are typically flagged as outliers in many statistical guidelines.

In a standard normal distribution, values beyond approximately +/-3 standard deviations from the mean are considered highly unusual, since about 99.7% of data should lie within that range under the empirical rule (68-95-99.7 rule). Therefore, a value with z < -3 or z > +3 stands apart from the bulk of the data.

The blank in the prompt is intended to be filled with the term that captures this idea of rarity or exception in the data set. The conventional term for such data points is outlier, which signals that the observation may warrant further investigation for data entry errors, measurement issues, or true rare events.

If you were to consider alternative terminology, you might encounter terms like anomaly or extreme value, but in standard statistical practice relating directly to z-scores and the empirical rule, outlier is the most appropriate label for these observations.

Since the question focuses on the thresholded z-score values and their classification, the key concept is that values beyond ±3 standard deviations are deemed outliers, highlighting their exceptional position relative to the data's central tendency.

Question at position 14 Any data value with a z-score less than –3 or greater than +3 is considered to be a(n) Question Blank 1 of 1[input].简答题

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Question at position 14 Any data value with a z-score less than –3 or greater than +3 is considered to be a(n) Question Blank 1 of 1[input].

To be an outlier in the boxplot above, a score must be:

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The five-number summary for the ages of the attendees at the Pawnee Harvest Festival is listed below. 1 20 29 38 80 I. There is at least one attendee whose age is a low potential outlier. II. There is at least one attendee whose age is a high potential outlier.

How many potential outliers are in the data?

Based on our in-class discussion, which of the following is not a potential cause of outliers?

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