The Excel KURT function returns the kurtosis of a data set — a measure of how heavy-tailed and peaked a distribution is relative to a normal curve. Excel returns excess kurtosis, so a normal distribution scores 0.
Syntax
| Argument | Description | |
|---|---|---|
number1 | Required | The first number, reference, or array. At least four data points are required. |
number2, ... | Optional | Up to 254 additional numbers or ranges. Empty cells, text, and logical values in a range are ignored. |
How to use it
Kurtosis describes the tails of a distribution. Excel reports excess kurtosis (kurtosis minus 3), so the benchmarks are:
| Result | Meaning |
|---|---|
| > 0 | Leptokurtic — heavier tails / sharper peak than normal |
| = 0 | Mesokurtic — tails like a normal distribution |
| < 0 | Platykurtic — lighter tails / flatter peak than normal |
KURT needs at least four data points; fewer returns #DIV/0!. The same happens if every value is identical (zero standard deviation).
Pair with SKEW: kurtosis describes tail weight; SKEW describes asymmetry. Together they summarize how far a distribution departs from a bell curve.
Try it: interactive demo
Pick a KURT example to see the formula and its result.
Practice workbook
Frequently asked questions
Does KURT return kurtosis or excess kurtosis?
What does a positive or negative KURT value mean?
How many data points does KURT need?
#DIV/0!.What is the difference between KURT and SKEW?
SKEW measures asymmetry — whether the distribution leans left or right. They describe different shape features.Master functions like this in one day
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