TSA Skewness and Kurtosis (Waveform) VI
- Updated2024-07-30
- 3 minute(s) read
Computes the skewness and kurtosis values of a univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.

Inputs/Outputs
![]() Xt specifies the univariate time series. ![]() error in describes error conditions that occur before this node runs. This input provides standard error in functionality. ![]() skewness returns the skewness value of the input time series. ![]() kurtosis returns the kurtosis value of the input time series. ![]() error out contains error information. This output provides standard error out functionality. |
TSA Skewness and Kurtosis Details
This VI calculates the skewness value according to the following equation:
where n is the number of samples of the input time series Xt, m is the arithmetic mean of Xt, and s is the standard deviation of Xt. Skewness is a symmetry measurement of the time series distribution. Negative values indicate left skewness. Positive values indicate right skewness.
This VI calculates the kurtosis value according to the following equation:
where n is the number of samples of the input time series Xt, m is the arithmetic mean value of Xt, and s is the standard deviation of Xt. Kurtosis is a peakedness measurement of the time series distribution. Kurtosis values close to 3 indicate normal-peak distribution. Kurtosis values less than 3 indicate a flatter distribution than normal distribution. Kurtosis values greater than 3 indicate a sharper distribution than normal distribution.
Examples
Refer to the Series Statistical Analysis VI in the labview\examples\Time Series Analysis\TSAGettingStarted directory for an example of using the TSA Skewness and Kurtosis VI.