Description Usage Arguments Details Value Author(s) References Examples
Performs skewness test for the composite hypothesis of normality, see, e.g., Shapiro, Wilk and Chen (1968).
1 | skewness.norm.test(x, nrepl=2000)
|
x |
a numeric vector of data values. |
nrepl |
the number of replications in Monte Carlo simulation. |
The skewness test for normality is based on the sample skewness:
√{b_1} = \frac{\frac{1}{n}∑_{i=1}^n(X_i - \overline{X})^3}{≤ft(\frac{1}{n}∑_{i=1}^n(X_i - \overline{X})^2\right)^{3/2}},
The p-value is computed by Monte Carlo simulation.
A list with class "htest" containing the following components:
statistic |
the value of the sample skewness. |
p.value |
the p-value for the test. |
method |
the character string "Skewness test for normality". |
data.name |
a character string giving the name(s) of the data. |
Ilya Gavrilov and Ruslan Pusev
Shapiro, S. S., Wilk, M. B. and Chen, H. J. (1968): A comparative study of various tests for normality. — Journal of the American Statistical Association, vol. 63, pp. 1343–1372.
1 2 | skewness.norm.test(rnorm(100))
skewness.norm.test(abs(runif(100,-2,5)))
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