Question

if a data set has only one outlier, which value will always change when the outlier is excluded? the median the range the interquartile range the upper quartile predicting the effects of an outlier

Explanation:

Step1: Understand the effect of an outlier

The median is the middle - value of a data - set. If the data - set has an odd number of values, the median is the middle number. If it has an even number of values, the median is the average of the two middle numbers. An outlier does not always affect the median, especially if the data - set is large.

Step2: Analyze the range

The range is calculated as the difference between the maximum and minimum values in the data - set. An outlier is an extreme value. When the outlier is removed, either the maximum or minimum (or both in some cases) value of the data - set changes, thus changing the range.

Step3: Analyze the inter - quartile range

The inter - quartile range (IQR) is the difference between the upper quartile (Q3) and the lower quartile (Q1). It is based on the middle 50% of the data. An outlier is an extreme value outside this middle 50% and usually does not affect the calculation of Q1 and Q3, so the IQR is not always affected.

Step4: Analyze the upper quartile

The upper quartile (Q3) is the value such that 75% of the data lies below it. An outlier may or may not affect Q3 depending on its position relative to the 75th percentile. If the outlier is an extremely large value and is removed, Q3 may change, but not always.

Answer:

the range