[M]-Outlier-Extraction-&-Removal-by-Observation.md

Outlier Extraction & Removal by Observation

1. Plot the data and identify outliers.
   • Density plot
   • Histogram
2. If required, remove outliers.

Preparation Code

# Functions
library(dplyr)

Actual Code

Sample Task 1

Extract observations of mtcars$hp above 300 (outliers).

M.age.outliers <- mtcars %>% filter(mtcars$hp > 300)

Sample Task 2

Remove observations of mtcars$hp above 300 (outliers).

M.age.wo <- mtcars %>% filter(mtcars$hp <= 300)