norm.test: Normality Test

In feranpre/udaicR: Basic functions that I use all the time

Normality Test

Description

This function assess if a variable follows the normal distribution. This is done using Shapiro-Wilk's test whenever possible and Lilliefor's correction for Kolmogorov-Smirnoff if Shapiro-Wilk's is not possible.

Usage

norm.test(
  variable,
  to.numeric = TRUE,
  decimals = 2,
  method = "auto",
  lang = "en",
  show.interpretation = FALSE,
  show.theory = FALSE,
  show.warnings = TRUE
)

Arguments

variable	vector (numeric if possible) of observations to for wich normality will be assessed
to.numeric	if the vector is not numeric: do you want to try an automatic conversion?
decimals	number of decimals for the p value (it will determine the threshold for "<x.xxx1" p value too)
method	string with the possible methods: "sw", "lille", "ks" (default: "auto")
lang	either "en" for english or "es" for spanish
show.interpretation	a logical value indicating if you want an interpretation of normality and the specific result you have
show.theory	a logical value indicating if you want a background explanation of the test
show.warnings	a logical value indicating wether you want warnings to be shown or not

Value

It returns list of elements: * var name of the variable tested * method method used to determine normality * p.value exact p value (rounded as per decimals argument) * p.value.str STRING value with p value. If p value < 10^-(decimals + 1) then returns "<0.(decimals)1". If decimals = 2 then <0.001 * normal logical value indicating if the variable follows a normal distribution or not * theory TEXT theory about normality test * interpret TEXT interpreting the results * config: + show.theory whether or not a theory explanation was solicited + show.interpretation whether or not an interpretation was solicited + lang languaje selected for the output

feranpre/udaicR documentation built on July 15, 2022, 12:54 p.m.