# example 3.2 of section 3.1.1 
# (example 3.2 of section 3.1.1)  : Exploring data : Using summary statistics to spot problems : Typical problems revealed by data summaries 
# Title: Will the variable is.employed be useful for modeling? 

is.employed         	# Note: 1 
 Mode :logical
 FALSE:73
 TRUE :599
 NA's :328

                       housing.type   	# Note: 2 
 Homeowner free and clear    :157
 Homeowner with mortgage/loan:412
 Occupied with no rent       : 11
 Rented                      :364
 NA's                        : 56


 recent.move      num.vehicles
 Mode :logical   Min.   :0.000
 FALSE:820       1st Qu.:1.000
 TRUE :124       Median :2.000
 NA's :56        Mean   :1.916
                 3rd Qu.:2.000
                 Max.   :6.000
                 NA's   :56

# Note 1: 
#   The variable is.employed is missing for 
#   about a third of the data. Why? Is employment status unknown? Did the 
#   company start collecting employment data only recently? Does NA mean “not in 
#   the active workforce” (for example, students or stay-at-home 
#   parents)? 

# Note 2: 
#   The variables housing.type, recent.move, 
#   and num.vehicles are only missing a few values. It’s probably safe to just 
#   drop the rows that are missing values—especially if the missing values are 
#   all the same 56 rows. 

