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.

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