A Function for computing univariate normality test on data frame.
Source:R/normality.loop.R
normality.loop.Rd
This function will compute normality on entire data set. Sometime in dlookr package p values turns out to be null thus failing to test normality of the data set. This is a good alternative of dlookr function. Here normality is tested using shapiro.test from base stats.
Arguments
- df
A data frame.
- bonf
If TRUE a bonferonni correction will be conducted.
- alpha
Desired alpha.
Examples
data <- tabledown::Rotter[, 11:31]
normality.loop(data)
#> $statistic
#> item2.W item3.W item4.W item5.W item6.W item7.W item9.W item10.W
#> 0.4687783 0.3984029 0.6346962 0.4389197 0.6054954 0.4115381 0.5840242 0.3173180
#> item11.W item12.W item13.W item15.W item16.W item17.W item18.W item20.W
#> 0.6362266 0.6342364 0.6349068 0.6342364 0.5789720 0.5018625 0.4835846 0.6364813
#> item21.W item22.W item23.W item25.W item26.W
#> 0.5375357 0.5708925 0.3509070 0.6016894 0.5621908
#>
#> $p.value
#> item2 item3 item4 item5 item6 item7
#> 2.653088e-35 6.227311e-37 1.248056e-30 5.155272e-36 1.462305e-31 1.219678e-36
#> item9 item10 item11 item12 item13 item15
#> 3.271646e-32 1.255529e-38 1.401678e-30 1.205368e-30 1.268128e-30 1.205368e-30
#> item16 item17 item18 item20 item21 item22
#> 2.320927e-32 1.781982e-34 6.146609e-35 1.429076e-30 1.562937e-33 1.349463e-32
#> item23 item25 item26
#> 6.027334e-38 1.116209e-31 7.593841e-33
#>
#> $significance
#> item2 item3 item4 item5 item6 item7 item9 item10 item11 item12 item13
#> "*" "*" "*" "*" "*" "*" "*" "*" "*" "*" "*"
#> item15 item16 item17 item18 item20 item21 item22 item23 item25 item26
#> "*" "*" "*" "*" "*" "*" "*" "*" "*" "*"
#>
#> $method
#> [1] "Shapiro-Wilks test with Bonferroni Correction"
#>