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KURT
KURT quantifies whether a distribution has heavier or lighter tails than a normal (bell curve) distribution: positive kurtosis (leptokurtic) indicates more extreme outliers, while negative kurtosis (platykurtic) indicates fewer. It is used in risk management and data quality assessments to detect fat-tailed behavior.
Excel
=KURT(A2:A5)Google Sheets
=KURT(A2:A5)Try it with your data
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How it works
- 1Assemble at least four numeric values in a range; KURT requires a minimum of 4 data points.
- 2Enter =KURT(range) to obtain the excess kurtosis (normalized to 0 for a normal distribution).
- 3Values above 0 suggest heavier tails with more outliers; values below 0 suggest lighter tails.
Need a version for your data?
Try: “Determine whether our daily stock return distribution has heavier tails than a normal distribution”