Quartiles divide a sorted dataset into four equal parts.
Q1 = 25th percentile. Q2 = median. Q3 = 75th percentile.
IQR = Q3 − Q1. Data below Q1 − 1.5×IQR or above Q3 + 1.5×IQR are outliers.
Reach for this tool when characterising data for research, quality control, or business analysis. The results follow standard statistical definitions and are compatible with further inferential analysis.
Many users interpret statistical results without considering the distribution of the data. Standard deviation is most meaningful for roughly normally distributed data — in highly skewed datasets, the median and IQR are more appropriate measures of centre and spread.
A teacher calculates the class average and standard deviation for an exam: mean 64%, SD 18%. The high SD suggests a wide spread of performance levels — indicating the class may need differentiated support rather than a single revision strategy.
IQR (Interquartile Range) = Q3 − Q1. It covers the middle 50% of your data.