Percentage of outliers at three z-score thresholds

Z-standardises vector and counts the percentage of observations whose absolute z-score exceeds 1.96, 2.58, and 3.29, corresponding approximately to the 95 %, 99 %, and 99.9 % tails of the normal distribution. Designed to be applied across columns with sapply.

Usage

outlier_summary(vector)

Arguments

vector

Numeric vector. Missing values are removed before the z-standardisation and the counts.

Value

A one-row data frame with three character columns:

abs_z_1.96

Percentage of observations with \(|z| \ge 1.96\).

abs_z_2.58

Percentage of observations with \(|z| \ge 2.58\).

abs_z_3.29

Percentage of observations with \(|z| \ge 3.29\).

Examples

vector <- generate_missing(rnorm(50), missing = 10)
df <- generate_missing(mtcars[, 1:2], missing = 10)
outlier_summary(vector)
#>   abs_z_1.96 abs_z_2.58 abs_z_3.29
#> 1      7.5 %        0 %        0 %
data.frame(sapply(mtcars, outlier_summary))
#>               mpg cyl disp     hp   drat     wt   qsec  vs  am gear   carb
#> abs_z_1.96 6.25 % 0 %  0 % 3.12 % 3.12 % 9.38 % 3.12 % 0 % 0 %  0 % 6.25 %
#> abs_z_2.58    0 % 0 %  0 % 3.12 %    0 %    0 % 3.12 % 0 % 0 %  0 % 3.12 %
#> abs_z_3.29    0 % 0 %  0 %    0 %    0 %    0 %    0 % 0 % 0 %  0 %    0 %