Description Usage Arguments Details Value Examples
kurtosis
calculates the Kurtosis
1 | kurtosis(x, na.rm = T)
|
x |
a numeric vector, matrix or a data.frame |
na.rm |
(logical) Should missing values be removed? |
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
returns a single value if x
is a vector, otherwise a named
vector of size = ncol(x)
.
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