test.kurtosis: Computes p-value for test of excess kurtosis

In statpsych: Statistical Methods for Psychologists

Computes p-value for test of excess kurtosis

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 excess kurtosis is positive, then the normality assumption can be rejected due to leptokurtosis. If the p-value is small (e.g., less than .05) and excess kurtosis is negative, then the normality assumption can be rejected due to platykurtosis.

Usage

test.kurtosis(y)

Arguments

y	vector of quantitative scores

Value

Returns a 1-row matrix. The columns are:

• Kurtosis - estimate of kurtosis coefficient

• Excess - estimate of excess kurtosis (kurtosis - 3)

• p - Monte Carlo two-sided p-value for test of zero excess kurtosis

Examples

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

# Should return:
#      Kurtosis  Excess      p
# [1,]   4.8149  1.8149 0.0385 

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