What is true regarding the interquartile range's effect from extreme scores?

The interquartile range (IQR) is a measure of statistical dispersion that describes the middle 50% of a dataset by calculating the difference between the first quartile (Q1) and the third quartile (Q3). One of the key properties of the IQR is its robustness to extreme scores or outliers.

When extreme scores are present, they tend to affect measures like the mean and the overall range of the data significantly; however, the IQR remains unaffected. This is because the IQR only considers the values in the first and third quartiles, thus ignoring the highest 25% and the lowest 25% of the dataset, which include the extreme scores. Therefore, the inclusion or exclusion of extreme scores does not change the values of Q1 and Q3, leading to the conclusion that the IQR is a reliable measure of central tendency and variability that is resistant to the influence of these outliers.

This characteristic makes the IQR a preferred measure in datasets where extreme values are present, as it more accurately reflects the spread of the central portion of the data.