Does the range of a set of data remain unaffected by extreme scores?

The distinction around the range in a set of data is crucial for understanding how extreme scores impact statistical measurements. The range is defined as the difference between the highest and lowest values in a dataset. Therefore, extreme scores, often referred to as outliers, directly influence both the maximum and minimum values in a dataset.

When extreme scores are present, they will either increase or decrease the range significantly, depending on whether they are particularly high or particularly low in relation to the other scores. This means that the presence of these extreme values can lead to a distortion in the representation of the data set's variability.

In fact, the very essence of the range being a measure of dispersion means it is sensitive to these extreme scores, unlike other measures such as the interquartile range, which focuses on the middle 50% of data and is not influenced by outliers. Consequently, the assertion that the range remains unaffected by extreme scores is false; extreme values will always have a considerable impact on the range of a dataset.