Why is the interquartile range (IQR) considered more reliable than the range in a box plot?

The interquartile range (IQR) is a measure of statistical dispersion that specifically focuses on the middle 50% of a dataset. By considering only the first and third quartiles, the IQR effectively captures the central tendency of the data while excluding the influence of extreme values or outliers. This quality makes it a more reliable measurement than the range, which is determined by the highest and lowest data points and can be heavily skewed by outliers.

In contrast, the range takes into account all data points and is therefore susceptible to extreme values, which may not represent the overall distribution of the data accurately. For instance, if a data set has a couple of exceptionally high or low values, the range could give a misleading impression of the data's spread.

Thus, focusing solely on the middle 50% allows the IQR to provide a more accurate reflection of the dataset's variability and consistency, making it a preferred measure in statistical analysis, especially when comparing different datasets or drawing conclusions about trends.