The Interquartile Range (IQR) serves as a vital statistic in data analysis, representing the middle 50% of data points and providing a clearer picture by minimising the influence of outliers. Calculated by subtracting the first quartile (Q1) from the third quartile (Q3), the IQR helps identify data variability and detect anomalies. Its applications span various fields, as illustrated in success stories from education, retail, and healthcare. For instance, schools have used the IQR to pinpoint struggling student groups, while retailers have tailored loyalty programmes for high-spending customers based on IQR analysis. By visualising data with box plots, contextualising results, and combining IQR with other statistics, both novices and seasoned analysts can harness its power for informed, data-driven decisions, unlocking insights that drive success.