Performs skewness test for the composite hypothesis of normality,
see, e.g., Shapiro, Wilk and Chen (1968).
Usage
skewness.norm.test(x, nrepl=2000)
Arguments
x
a numeric vector of data values.
nrepl
the number of replications in Monte Carlo simulation.
Value
A list with class "htest" containing the following components:
statisticthe value of the sample skewness.
p.valuethe p-value for the test.
methodthe character string "Skewness test for normality".
data.namea character string giving the name(s) of the data.
Details
The skewness test for normality is based on the sample skewness:
$$\sqrt{b_1} = \frac{\frac{1}{n}\sum_{i=1}^n(X_i - \overline{X})^3}{\left(\frac{1}{n}\sum_{i=1}^n(X_i - \overline{X})^2\right)^{3/2}},$$
The p-value is computed by Monte Carlo simulation.
References
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.