test.skew: Computes p-value for test of skewness

In statpsych: Statistical Methods for Psychologists

Computes p-value for test of skewness

Description

Computes a Monte Carlo p-value (250,000 replications) for the null hypothesis that the sample data come from a normal distribution. If the p-value is small (e.g., less than .05) and the skewness estimate is positive, then the normality assumption can be rejected due to positive skewness. If the p-value is small (e.g., less than .05) and the skewness estimate is negative, then the normality assumption can be rejected due to negative skewness.

For more details, see Section 1.23 of Bonett (2021, Volume 1)

Usage

test.skew(y)

Arguments

y	vector of quantitative scores

Value

Returns a 1-row matrix. The columns are:

• Skewness - estimate of skewness coefficient

• p - Monte Carlo two-sided p-value

References

\insertRef

Bonett2021statpsych

Examples

y <- c(30, 20, 15, 10, 10, 60, 20, 25, 20, 30, 10, 5, 50, 40, 95)
test.skew(y)

# Should return:
# Skewness     p
#   1.5201 0.007

statpsych documentation built on Jan. 13, 2026, 1:07 a.m.