KURT.S OpenBI

How heavy the tails of a column's numbers are, taken as a sample: the sample excess kurtosis, as Excel's KURT.

Excess kurtosis compares the tails with a normal distribution's, which scores 0: positive means more values far out than a bell curve would have, negative fewer (a flat, even spread).

Group: Aggregation. OpenBI’s own: DAX has no function of this name.

Syntax

KURT.S ( <ColumnName> )

Returns

Number. The sample excess kurtosis of the column's values in the filter context; BLANK for fewer than four values, or when they are all equal.

Remarks

• The sample excess kurtosis, the one Excel's KURT gives: from the population's figure g (KURT.P) for n values, ((n + 1) × g + 6) × (n − 1) ÷ ((n − 2) × (n − 3)).
• Blanks are left out. Fewer than four values, or values that are all the same, give BLANK.
• A small sample's kurtosis jumps around a lot: read it with the number of values beside it.

Compared with DAX

An OpenBI function: DAX has none like it, so a measure or query that uses it works in OpenBI only, not in Power BI or Analysis Services.

Excel's KURT gives the same number for the same values.

Examples

Monthly liters of every shop and product

The sales rows (a month, a shop, a product each) and how their liters spread.

EVALUATE
ROW (
    "Rows", COUNT ( Sales[Liters] ),
    "Skewness", SKEW.S ( Sales[Liters] ),
    "Excess kurtosis", KURT.S ( Sales[Liters] )
)

Too few values

Three beers are not enough for a sample's kurtosis; the population's has a value.

EVALUATE
ROW (
    "Sample", CALCULATE ( KURT.S ( Products[Price per liter] ), Products[Category] = "Beer" ),
    "Population", CALCULATE ( KURT.P ( Products[Price per liter] ), Products[Category] = "Beer" )
)

Related functions

KURT.P, KURTX.S, SKEW.S, STDEV.S.

Last updated 8 November 2026 · OpenBI Studio 0.3.78