# kurtosis: Kurtosis In analyzer: Data Analysis and Automated R Notebook Generation

## Description

kurtosis calculates the Kurtosis

## Usage

 1 kurtosis(x, na.rm = T) 

## Arguments

 x a numeric vector, matrix or a data.frame na.rm (logical) Should missing values be removed?

## Details

This function calculates the kurtosis of data which is a measure of the "tailedness" of the probability distribution of a real-valued random variable. Like skewness, kurtosis describes the shape of a probability distribution. The formula used is:

\frac{E[(X-μ)^{4}]}{( E[(X-μ)^2])^{2}}

. This formula is the typical definition used in many older textbooks and wikipedia

## Value

returns a single value if x is a vector, otherwise a named vector of size = ncol(x).

## Examples

 1 2 3 4 5 # for a single vector kurtosis(mtcars\$mpg) # for a dataframe kurtosis(mtcars) 

analyzer documentation built on July 1, 2020, 10:02 p.m.