Loading…
Loading…
SigmaCalc
Split your data into four equal parts and spot the outliers.
Q1 is the value below which 25% of the data falls, Q2 is the median (50%), and Q3 marks 75% — the interquartile range (Q3 − Q1) captures the middle 50% of your data, ignoring extreme tails entirely.
Any value below Q1 − 1.5×IQR or above Q3 + 1.5×IQR is flagged as a statistical outlier — this is the same rule that draws the whiskers on a box plot, and it's far more resistant to extreme values than a simple standard-deviation cutoff.
What you entered
Sort the dataset
10 values= 7, 15, 36, 39, 40, 41, 42, 43, 47, 49Q1 (25th percentile)
lower quarter= 36.75Q2 (median, 50th percentile)
middle value= 40.5Q3 (75th percentile)
upper quarter= 42.75Interquartile range: Q3 − Q1
42.75 − 36.75= 6Outlier fences: Q1/Q3 ± 1.5×IQR
36.75 − 1.5×6, 42.75 + 1.5×6= [27.75, 51.75]Result
IQR: 6
The interquartile range is 6 — any value outside [27.75, 51.75] is a statistical outlier by the 1.5×IQR rule.