The KURT function returns the kurtosis of a data set. Kurtosis characterizes the relative peakedness or flatness of a distribution compared with the normal distribution.

Two types of kurtosis exist. They are −

- Positive kurtosis indicates a relatively peaked distribution.
- Negative kurtosis indicates a relatively flat distribution.

**Syntax**:= KURT(number1, [number2], …)

The KURT function syntax has the following arguments:

**Number1, number2, …**Number1 is required, subsequent numbers are optional. 1 to 255 arguments for which you want to calculate kurtosis. You can also use a single array or a reference to an array instead of arguments separated by commas.

**Example**: Let’s look at some Excel KURT function examples and explore how to use the KURT function as a worksheet function in Microsoft Excel:

Column A has an array of data. The kurtosis of this data can be calculated using the Excel Kurt function.

**Syntax**: =KURT(A2:A16)

**Result**: 0.573517392

This gives the result 0.573517392, indicating a distribution that is relatively peaked (compared to the normal distribution).

**Note**:

- Arguments can either be numbers or names, arrays, or references that contain numbers.
- Logical values and text representations of numbers that you type directly into the list of arguments are counted.
- If an array or reference argument contains text, logical values, or empty cells, those values are ignored; however, cells with the value zero are included.
- Arguments that are error values or text that cannot be translated into numbers cause errors.
- If there are fewer than four data points, or if the standard deviation of the sample equals zero, KURT returns the #DIV/0! error value.
- Kurtosis is defined as:

where s is the sample standard deviation.