norm_test_fun: Checks for Normality Assumption

In analyzer: Data Analysis and Automated R Notebook Generation

Description

norm_test_fun checks for the normality assumption

Usage

norm_test_fun(x, method = "anderson", pval = 0.05, xn = "x", bin = FALSE)

Arguments

x	a numeric vector
method	shapiro for Shapiro-Wilk test or 'anderson' for 'Anderson-Darling' test of normality or ks for 'Kolmogorov-Smirnov'
pval	significance level for normality tests. Default is 0.05
xn	vector name
bin	TRUE if only TRUE/FALSE is required

Details

This function checks for normality assumption using shapiro, Kolmogorov-Smirnov or Anderson Darling test. If the parameter bin is TRUE, then TRUE is returned if vector is normal, otherwise FALSE. The significance level is passed through the parameter pval

Value

Logical TRUE/FALSE based on the performed test and pval. If the vector follows the normality assumption, then TRUE is returned

See Also

anderson.test for Anderson Darling test

Examples

norm_test_fun(mtcars$mpg)
norm_test_fun(mtcars$mpg, method = "shapiro",
              pval = 0.05, xn = "mpg", bin = TRUE)

analyzer documentation built on July 1, 2020, 10:02 p.m.