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.

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 for test of zero skewness

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,]   1.5201 0.0067

statpsych documentation built on July 9, 2023, 6:50 p.m.