The Interquartile Range (IQR) represents the spread of the middle 50% of a dataset. It is determined by subtracting the first quartile (Q1, the 25th percentile) from the third quartile (Q3, the 75th percentile). In spreadsheet software, this statistical measure can be efficiently determined using built-in functions. For example, if a dataset is in column A, from row 1 to row 100, the first quartile can be found using the formula `=QUARTILE.INC(A1:A100,1)` and the third quartile with `=QUARTILE.INC(A1:A100,3)`. Subtracting the result of the first formula from the second yields the IQR.
Understanding the IQR is beneficial for identifying data variability and outliers. A smaller IQR indicates data points are clustered more closely around the median, while a larger IQR suggests greater dispersion. This metric is less sensitive to extreme values than the range, making it a robust measure of statistical dispersion. Its use dates back to early statistical analysis and remains relevant for summarizing data distributions across diverse fields, including finance, healthcare, and engineering.