The first method — is.na() is.na tests the presence of missing values or null values in a data set. The method searches through every single column of the dataset, finding outliers with a na value that might affect the calculation. Example;``` x <- c(1,2,3,4,NA) is.na(x) returns a series of FALSE and TRUE depending on whether…