In chrsshn/checknormality: Check the Normality of Data Using Statistical Tests

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
) 
set.seed(80)

checknormality: because you should always check your assumptions

Overview

The goal of checknormality is to provide implementations of popular normality tests that return the test statistics and p-values. As of 2020/11/30, the package contains an implementation of the Shapiro-Wilk Test of Normality.

A Note on the Algorithms

Shapiro-Wilk Test

• For n > 50, the J. P. Royston approach for the Shapiro-Wilk test as described here must be used.

• For 3 <= n <= 50, there are three "approaches": the original approach for the Shapiro-Wilk test as described here, a modified approach that is compatible with the Royston approach as described in the last paragraph here, and the Royston approach for n > 20.

Inverse of Normal CDF (Phi inverse)

• The Royston approach requires the inverse of the normal CDF, which is calculated in R using

stats::qnorm(p)

• In the Rcpp implementation of the Royston approach, a freely-available stand-alone C++ implementation was used.

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("chrsshn/checknormality")

Usage

Example 1: Testing a small sample from an exponential distribution using the original, modified, and Royston approaches

set1 <- rexp (30, .8)
checknormality::sw_test (set1, "original")
checknormality::sw_test (set1, "modified")
checknormality::sw_test (set1, "royston")
stats::shapiro.test (set1) 
plot(density (set1))

Note: you can also get the W test statistic using the functions checknormality::R_get_W () and checknormality::C_get_W()

Example 2: Testing a small sample from a normal distribution using the original, modified, and Royston approaches

``` {r echo = T, eval = T} set2 <- rnorm (40, 20, 5) checknormality::sw_test (set2, "original") checknormality::sw_test (set2, "modified") checknormality::sw_test (set2, "royston") stats::shapiro.test (set2) plot(density (set2))

### Example 3: Testing a large sample from a Poisson distribution using the Royston approach
note: the original and modified approaches are only valid for n < 50 points
``` {r echo = T, eval = T}
set3 <- rpois(4000, .787)
checknormality::sw_test (set3, "royston")
stats::shapiro.test (set3)
plot(density (set3))   

Example 4: Testing a large sample from a normal distribution using the Royston approach

note: the original and modified approaches are only valid for n < 50 points ``` {r echo = T, eval = T} set4 <- rnorm(4000) checknormality::sw_test (set4, "royston") stats::shapiro.test (set4) plot(density (set4))

```

chrsshn/checknormality documentation built on Dec. 31, 2020, 10:01 p.m.