# How do you know if data is normally distributed with skewness and kurtosis?

## How do you know if data is normally distributed with skewness and kurtosis?

Statistically, two numerical measures of shape – skewness and excess kurtosis – can be used to test for normality. If skewness is not close to zero, then your data set is not normally distributed.

**What is the skewness and kurtosis of a normal distribution?**

A symmetrical dataset will have a skewness equal to 0. So, a normal distribution will have a skewness of 0. Skewness essentially measures the relative size of the two tails. Kurtosis is a measure of the combined sizes of the two tails.

### Can you calculate skewness in Excel?

Excel Function: Excel provides the SKEW function as a way to calculate the skewness of S, i.e. if R is a range in Excel containing the data elements in S then SKEW(R) = the skewness of S. This version has been implemented in Excel 2013 using the function, SKEW.

**Does Excel calculate kurtosis or excess kurtosis?**

Excel’s kurtosis function calculates excess kurtosis.

## How do you interpret kurtosis in Excel?

Returns the kurtosis of a data set. Kurtosis characterizes the relative peakedness or flatness of a distribution compared with the normal distribution. Positive kurtosis indicates a relatively peaked distribution. Negative kurtosis indicates a relatively flat distribution.

**Which test use skewness and kurtosis to check for normality?**

Normality tests based on Skewness and Kurtosis The following two tests let us do just that: The Omnibus K-squared test. The Jarque–Bera test.

### How do you find kurtosis in Excel?

Excel’s kurtosis function calculates excess kurtosis.

- Enter the data values into cells.
- In a new cell type =KURT(
- Highlight the cells where the data are at. Or type the range of cells containing the data.
- Make sure to close the parentheses by typing )
- Then press the enter key.